How to Integrate AI Tech Into Each Step of the Customer Journey

The Customer Lifecycle. The Sales Funnel. The Buyer’s Journey. All of these phrases are similar expressions of the same thing. They’re used to describe the process that it takes for a visitor to become a customer.

The Customer Lifecycle. The Sales Funnel. The Buyer’s Journey. All of these phrases are similar expressions of the same thing. They’re used to describe the process that it takes for a visitor to become a customer.

While the models and names of stages may have changed through the years, many agree that it can be boiled down to four simple components:

Awareness > Consideration > Decision > Loyalty

The No. 1 goal for most businesses is to generate more conversions (which primarily consists of sales). This can be through their marketing efforts, sales tactics, brand communication, conversion rate optimization, and other methods. Of late, many companies have developed critical competencies in using AI to nudge customers towards sales, and have improved their numbers drastically as a result.

AI, machine learning, and big data technology can all work hand-in-hand to improve the customer experience and support an optimized customer journey, which leads to more conversions in several key ways.

Let’s talk about how you can start using AI tech in each stage of the funnel.

Awareness

Marketing strategies these days are often heavily focused on the top of the funnel to build brand awareness and attract new customers. For many businesses, recognition is nearly equivalent to the value of their brand. Elena Veselinova and Marija Gogova Samonikov explain in their book Building Brand Equity and Consumer Trust Through Radical Transparency Practices that brand impact is a continuous process that insures purchases, cash flow, revenue and share value. Brand communication and experience creates and builds a loyal base of customers that do not consider any other brand.

Creating a strong level of brand awareness takes time and strategy. Companies spend millions of dollars on marketing campaigns and advertising to increase their reach and recognition, but AI tech is able to take the guesswork out of these strategies by analyzing huge volumes of consumer data for more targeted campaigns. For example, predictive analytics software can collect, track, and analyze datasets from past customers to determine which strategies or tactics performed well. These datasets are turned into reports with insights to guide marketing efforts and place relevant content in front of the most interested eyes at the right times.

With AI-assisted marketing, advertising strategies can be backed with data to optimize ad placement. Machine learning systems can even identify the best influencers for brands to partner with in order to reach relevant audiences and grow brand familiarity.

Credit: Venturebeat.com

Consideration

The next step of the buyer’s journey is often overlooked by marketers because it can drag on for a long time, depending on the product and the customer’s needs. During the consideration phase, a customer is already familiar with a brand or product but are unsure of whether or not to actually purchase. Customers will typically research the product’s reviews, compare prices to competitors, and look for alternatives during this stage. Due to this, the number of potential customers tends to narrow down considerably as they move from this step to the decision phase.

Brands must work to combat each customer’s concerns and questions standing in the way of a purchase decision. One of the best ways to do this is by offering personalized content that is relevant to each person, making it easy for them to find the information they are seeking.

AI systems can be used to predict a customer’s needs based on consumer data and previous online behavior, and then encourage conversions with a tailored UX or even a completely customized landing page that displays content relevant to that customer.

For example, if a site visitor has viewed a certain product page and played a video demonstrating its features, these actions can trigger an AI system to target them with personalized content that prompts a conversion if they don’t proceed to buy immediately. This content could be something as simple as an email message with more information or a display ad with a special offer for the specific product.

Credit: Personyze.com

Then there are platforms that use conversational AI tech (such as chatbots and voice assistants) to power automated, text- or audio-based interactions between a business and its customers. These platforms can understand speech, decipher intent, differentiate between languages, and mimic human conversations with great accuracy. Increasingly, they are advanced enough to even understand individual context and personalize the conversation accordingly.

Based on data insights, AI tech can curate content that matches up with the issues that are most important to that person, whether it be product features, immediate delivery, long term savings, etc. Customers respond quite well to personalized offers — an Accenture study reported that 91% of consumers are more likely to purchase from a company that sent them targeted deals or recommendations.

Decision

Once a customer moves from consideration to action, AI tools can be used to support a positive sales experience and eliminate any bumps along the way. If a customer encounters an issue while browsing the site, or during checkout or payment, it could be an instant sales killer, if it isn’t handled immediately by something like live chat.

According to multiple studies, one of the most frustrating parts about online customer service is long wait times. By using AI-enabled chatbots, companies can instantly answer common questions and resolve issues or roadblocks affecting the progression of the buyer’s journey. And customers certainly appreciate these quick response times. AI systems can significantly increase conversions with effective personalization and swift customer service.

Credit: AIMultiple.com

Loyalty

The last step of the customer journey is possibly the most valuable. Over half of customers reportedly stay loyal to brands that “get them.” Returning customers also tend to spend more money than new ones, and an oft-reported stat says that on average 65% of businesses’ revenue comes from existing customers.

Businesses (and customers) can benefit greatly from loyalty programs that are backed with machine learning technology. Starbucks famously uses AI tech to analyze customer behavior, improve convenience, and identify which promotions would perform best based on that person’s drink or food preferences, location, and purchase frequency. Their loyalty program uses this data to send out thousands of offers each day for the products their customers are most likely to buy. Their customer loyalty program grew 16% YoY last year as a direct result of their Deep Brew AI engine.

Credit: Starbucks app

While a positive shopping experience and great products are certainly important factors in a customer’s decision to buy again, data-driven marketing campaigns that encourage loyalty can also help a company to grow their numbers of repeat sales. Again, AI-assisted personalization techniques can boost the chances of a customer coming back for more, especially if they receive targeted offers or shopping suggestions based on previous interactions.

Credit: Accenture.com

The Wrap

AI is proving to be the tool of the future for marketers. It allows marketing teams to use predictive insights and analytical data to encourage and assist every micro-decision taken by consumers. AI systems not only help customers move along the buyer’s journey, they can also provide a more meaningful experience along the way, leading to more conversions and brand loyalty down the road.

Are You Taking a 360 Degree View of Content Marketing?

Creating content that relates to customers and builds engagement has consistently been the top challenge for marketing departments. Many marketers feel like they’re just shooting in the dark in terms of content marketing — sometimes it works and sometimes it doesn’t.

Creating content that relates to customers and builds engagement has consistently been the top challenge for marketing departments. Many marketers feel like they’re just shooting in the dark in terms of content marketing — sometimes it works and sometimes it doesn’t. This is especially true for teams that are trying to increase sales by building brand authority in their industry.

So here are some critical questions that CMOs and content managers can ask themselves to determine if their strategy is on the right track, confirm whether they’re sticking to the fundamentals and make sure they aren’t making any obvious mistakes.

Is Your Messaging in Tune With Industry Buzz?

Keeping your company’s marketing content relevant and interesting doesn’t mean that you should pursue every trend that passes by. However, that doesn’t mean you can simply dismiss all of them either. Content must either be unique or refer to current events fresh in people’s minds in order to keep their attention, regardless of how informative it is. By keeping up with the latest news and updates specific to your industry or niche, you could be one of the first outlets to provide an opinion on them.

Great content marketing and SEO go hand-in-hand, so in order to make your content seen and heard, it must include the terms, slang and even jargon that might draw in relevant audiences. By keeping up with the latest conversations and expressions being thrown around, you can tweak your content to identify more closely with your target audience.

Google’s Trends tool can help you monitor the keywords and topics being searched for and discussed online. It also shows you the volume of these searches and how fast interest in a given topic is rising or waning.

Credit: Trends.Google.com

Don’t just latch on to any topic that is trending in your area of reference. Be sure that it is relevant to an audience in your niche and that you understand what it is all about, and are able to share insights or at least use it in an entertaining way

Once you find the kind of themes and issues that your pique your audience’s interests, you can nail down a direction and certain ideas around which to build your brand messaging.

Are You Letting Your Audience Guide Your Content Strategy?

In order to let your audience and customers drive your ideation and approach, you must make sure you know them through and through, so that you can create the most relevant and engaging content. This is best done by formulating audience personas to help get into the mind of your typical consumer. You will need to delve deep into the demographics and analytical data to create generalizations about the type of people that follow your brand.

  • What do they look like?
  • How do they speak?
  • What buzzwords are they familiar with?
  • Where and how do they consume content?
  • What industries do they work in?

Create multiple personas. These generalities can then be used to guide content by focusing on the subjects that would likely appeal to these different personas. For example, Customer A may be more interested in the nitty-gritty details of your industry, while Customer B might be more interested in learning practical ways to use your products or services. Customer A might place a premium on your brand experience while Customer B might just be looking for the cheapest product around.

Credit: Hop.online

Perhaps the most important ingredient to a fresh content strategy is simply knowing who you are communicating with and how to do so effectively.

Are You Analyzing Visitor Behavior on Your Website to Understand Intent?

The role of big data in content marketing cannot be underestimated. To stay competitive, businesses and marketers need to understand that they’re operating in a competitive environment that needs constant adjusting and optimization. Whenever a landing page is tied to a piece of content, blog post, email or even social media update, you need to know exactly how it performs in relation to your goals.

Before you even begin designing or optimizing your landing page, you must first ask yourself: why are customers coming to this specific page? What do they intend to get out of it and what are they looking for?

Marketers need not wait for coders or designers to develop or customize a landing page. Tools such as Landingi offer easy ways to add a quick page with forms, text boxes, drop downs, buttons and other elements to help you optimize your marketing funnel and automate the user workflow on your site.

Take a sign up page for example. You can easily create a form to gather information that tells you more about your audience. This can as simple as their location, most pressing concern, or how they discovered your brand. Using this data, you can refine your sales approach in a way that resonates with current or potential leads.

Remember that the intent of visitors is not always (read, almost never) to purchase. On the contrary, the majority of your first-time visitors will be looking for information on what your company or product does, how much it costs, and so on. You need to create exact content so that each landing page fulfills a specific purpose.

One great place to start is by answering common questions that visitors are asking. You can find these through intent-based keyword research for more general topics or you can address issues that customers frequently raise with your support or service team.

Kapost used this strategy to great effect by sharing information directly from their sales and customer service team’s conversations with their marketing department. Their content team then created specific pages for these questions so that future customers could instantly find this information and they could create more relevant landing pages.

Credit: Kapost.com

You can also experiment with different variations of your landing pages through split testing. Consistently testing components like style, copy, and CTA buttons will give you plenty of data-backed insights as to what makes your audience tick.

Are You Using Events and Experiences to Create Content?

Your business events can provide a plethora of valuable inspiration that can be used and reused to support a sustainable content marketing strategy. You can also use these insights in future promotions with value-based messaging.

Ecommerce platform Shopify teamed up with Kylie Jenner to promote her temporary pop-up shop as well as their retail POS system. While there was a lot of marketing buzz promoting Kylie Cosmetics during the event, Shopify pulled the online equivalent of a guerilla marketing stunt by telling the story to their customers through their blog.

They published a post talking about all that goes into the planning of offline experiences for online businesses and the power it has. They even shared some behind-the-scenes pictures and details about Kylie’s store. The story was by no means blatantly promotional, but instead it had some real-life applications and valuable insights for retail business owners – Shopify’s core audience.

Credit: Shopify.com

Don’t be fooled. The entire piece was marketing content for their own company. Shopify used the event as an opportunity to mention their new POS system that Kylie Cosmetic used in order to handle all of the transactions during the pop-up. They even snapped a photo of Kylie herself using the system.

By turning a business event into marketing content, you can not only provide your audience with great information and examples, you can also promote your product’s usefulness through effective storytelling.

While statistics and numbers are great for proving points and communicating research, studies have found that when content tells an actual story and provides a practical application, it resonates far more with audiences and produces better results, eventually boosting conversion rates in the process.

Over to You

Consumers are more than an accumulation of facts and figures; and so must be your marketing strategies. There is so much pressure in the marketing world to deliver sales, to come out with the most innovative, creative, and unique strategies that marketers have lost focus on what is truly important: the customer experience.

Through content marketing, organizations are now able to build real connections with their customers as well as a larger audience in a way that was never before possible. The best content marketing strategies don’t necessarily depend on budgets or technology; they’re tied to brand-customer relationships.

As a marketer, it your job to empower your brand to build these relationships and facilitate experiences that bring positive results. The best way to do this is to give customers information that they can actually use – and make sure they use it!

How to Make Actionable Sense of Customer Sentiment Analysis

Creating a better customer experience is a top priority for most businesses, with 72% of companies saying improving CX is their No. 1 goal, according to data from Forrester. However, figuring out what drives a better user experience is a total guessing game, unless you take a deep dive into customer sentiment analysis.

Creating a better customer experience is a top priority for most businesses, with 72% of companies saying improving CX is their No. 1 goal, according to data from Forrester. However, figuring out what drives a better user experience is a total guessing game, unless you take a deep dive into customer sentiment analysis.

Understanding the responses and reactions that customers give out after using your products can help your brand immensely. Of course, conducting market research and surveys, and gathering feedback from customers are all small but essential steps toward improving your product or service, as well as its user experience. However, these reports are mostly a whole lot of confusing numbers and statistics; they offer no action plan or recommendations, or even insights on what to do next.

Making actionable sense of the numbers can be tricky, especially if there are no clear problems or opportunities that were identified through your research.

So, what should you do? Let’s go step-by-step.

Pinpoint Common Threads in Customer Reviews

While it’s typically a company’s first reaction to try to remove negative reviews that could deter future customers, these actually may be your best resource for fixing hidden issues.

About 25% of consumers have left a review for a local business because of a bad experience, but this doesn’t mean that 100% of these reviews are helpful to either companies or other customers. It’s best to turn to a reliable system here that can sift through emotionally exaggerated (and practically useless) or downright fake reviews and uncover valuable information that could point you toward better solutions.

A review platform, such as Bazaarvoice, allows brands to collect genuine ratings and reviews from customers, respond to their questions and concerns about their products, display moderated content created by customers on social media, and even implement a product sampling program based on the reviews you’ve collected.

Similarly, an interaction management tool, like Podium, gets you in the game earlier, helping you connect and interact with prospects on multiple channels. It enables team collaboration on lead generation and nurturing, as well as solving customer problems, leading to a consistent customer experience.

Customer Sentiment Analysis image
Credit: Podium.com

More customers tend to leave reviews with brands that use customer review management tools. This results in more data for your sentiment research, eventually ensuring better targeting and success of your product marketing campaigns.

Watch out for repeated keywords throughout these reviews, such as issues with customer service, packaging, delivery, or pricing. Looking for patterns in your customer reviews lies at the core of identifying the problems and coming up with solutions.

Use Smart Segmentation

Customers never fit into the one-size-fits-all category. Even if you cater to a small niche or if your product has a very specific use, there will be subsets, segments, and cohorts, all influenced by varying demographics and regulations, who could affect opinions of your business. This is why smart segmentation is important when reviewing customer sentiment analysis.

Again, these segments may need different targeting strategies, depending on whether your company is a B2C or B2B entity.

B2C

B2C marketers need to look at the:

  • age:
  • location:
  • income: and
  • in-the-moment needs of their customers.

B2B

B2B marketers, on the other hand, need to address non-personal variances, such as:

  • company size:
  • budget; or
  • objectives.

By pairing demographic and quantitative data, customer sentiment may make more sense and provide even deeper insight than before. For instance, customers who are motivated by finding the best deal may say that your shipping costs are too high; whereas, customers with FOMO may be ready to pay extra for next-day delivery. When you have multiple datasets of behavioral data that you can compare against one another, your team can understand how to cater to various customer segments by understanding their motivations.

Note that customer “segments” vary from “profiles” or “personas.” They are not as specific, and typically only focus on one or two variables rather than a list of unique qualities. There are countless ways to segment your audience, so be sure to find the segmentation model that best fits your business.

Customer Sentiment Analysis photo
Credit: MeaningCloud.com

Identify Engagement Intent

Understanding the “why” behind your customer’s actions will shed some light on their sentiment reactions. Your expectations always influence your experience, so a customer’s engagement intent could play a part in their response.

The rise of search as a marketing channel has made it clear that there are essentially four engagement intent categories that consumers fall into today:

  • informational;
  • navigational;
  • commercial; and
  • transactional.

Each of these steps correlates well with the traditional AIDA sales funnel model.

Informational

The first is searching for information on a particular subject that may or may not be a problem for them. These are typically prospects who are just entering the marketing funnel. They simply want to know more, so if your website does not offer the information they are looking for, their interest in your brand or product will not develop at all.

Navigational

People in the navigational category are looking for a specific product, service, or piece of content. This group knows what they want, and they will be easily frustrated if they can’t find it.

Commercial

The commercial investigation intent group is interested in buying, but they just aren’t quite ready yet or aren’t convinced that your product offers the best solution for them. They fall just above the action segment of the sales funnel and are often looking for the last bits of information before they make a purchase.

Transactional

And finally, the transactional group has the intent to buy. They have already made their decision to buy a specific product; however, any hiccups in the buying or checkout process could deter them.

Identifying Engagement Intent

Of course, identifying their engagement intent is a little tricky, especially after the interaction has been completed. But with some digging and martech tools, there are ways to figure out the motivations behind every brand-customer engagement.

One of the clearest ways to identify engagement intent is through carrying out intent research, attribution modeling, and analyzing their behavior on your digital property. If they just read a post on your blog, chances are they were looking for more information on a topic related to your industry. If they clicked an ad and filled up a form on your landing page, they are probably interested in availing themselves of your service.

Once their intent has been identified and understood, it will be much easier to understand their sentiment post brand engagement or product usage.

Experiment With Changes

Finally, the only way to make customer analysis actionable is to, well, take action. However, just switching things up without constantly analyzing the results will only put you back at Square One.

Many marketers rely on A/B/n or multivariate testing strategies to compare different changes, whether it be in the design or layout to an entire product or service experience. However, A/B testing can be a long and arduous process that yields murky results. It may even mislead you, if you over-rely on seasonal or contextual variables. Unsurprisingly, AI technology has been a huge help in the A/B testing realm by improving the accuracy and reliability of the process, resulting in few conversion opportunities lost.

AI-based algorithms are able to gather and analyze massive amounts of data at a time. They can compare results of multiple tests against each other simultaneously at various interaction points along the buyer journey.

Tools like Evolv use machine learning (ML) to find which experiences and customer journey paths work best (make profits) for you and nudge customers down those paths accordingly. You can set up experiments on your landing pages with goals and KPIs, and let the algorithm tweak the UX for each customer by presenting various combinations. The data from these experiments help you understand how satisfied the customer is with the interaction, and also develop new hypotheses to keep testing further or make decisions related to product development or service delivery.

The Way Ahead

By understanding the root causes behind your customer’s reactions and feelings, you can go as far as to influence sentiment, improve brand loyalty ,and encourage advocacy. Always be looking for overlaps and commonalities among complaints. This will help you avert PR disasters, deliver exceptional customer service, and stay ahead of the competition.

Use sentiment analysis to understand where your customers are coming from by segmenting them and uncovering their intents at every interaction. Finally, track the effects of all your initiatives and take action responsibly to ensure they stay delighted at all times.

3 Ways to Derive Actionable Sales Insights From Content Marketing Data

Nearly all businesses these days are aiming to build content marketing strategies that enable them to “rise above the crowd” or “be heard above the noise.” Whether they’re succeeding or not is anyone’s guess. The trick with content marketing data is to know how each dataset feeds into the bottom line.

As we ring in 2020, talking about the importance of content marketing and why every brand should be doing it is a record that has been broken for quite some time.

Nearly all businesses these days are aiming to build content marketing strategies that enable them to “rise above the crowd” or “be heard above the noise.” Whether they’re succeeding or not is anyone’s guess. What’s for sure is that branded content campaigns are yielding copious amounts of big data about customers and their behaviors. Whether it’s web traffic, conversion rates, or engagement levels, the trick with content marketing data is to know how each dataset feeds into the bottom line.

With so much data being created and collected every day, it can be very difficult and overwhelming to translate this information into sales insights. In fact, one of the biggest challenges marketers face is associating content with revenue:

marketers' top challenges
Credit: MarketingCharts.com

So how can you show ROI from content marketing without letting your head spin from data overload? Let’s find out.

1. Unify Data Streams

Data collection is only getting more complex as sources and systems continue to grow. Depending on how far-reaching your content strategy is, the data streams that relate to your sales regime won’t always yield black and white answers. Therefore, market research data, customer data, and pretty much all company data should be unified in a single ecosystem. This will let decision-makers spot key trends that tie directly into the bottom line.

For example, you need to know things like the content channels that are bringing in the strongest leads, the common threads among your most profitable customer profiles, the types of content that get the most engagement, where your referrals are coming from, and so on.

Marketers these days are growing increasingly dependent on the constantly-growing number of data sources. The major tasks at hand involve monitoring, analyzing, and finding benchmark performances for each campaign.

Until recently, it was a huge (and expensive) effort to develop tool integrations that aligned content marketing data sources in ways that boosted the sales process. Thankfully, AI-enabled business intelligence and CRM platforms allow businesses to efficiently analyze their data streams. One such tool is Salesforce’s Einstein, which can unify company data to identify new audiences, deliver sales projections, create in-depth customer profiles, and even automate storytelling.

Salesforce Einstein
Credit: Salesforce.com

AI-based content platforms are designed to score touchpoint information to discover patterns that help determine which leads are likely to convert. They can create associations between varied data sets, such as website engagement and publicly available demographic information, for example, and turn these into stories.

The way you set up these stories determines which datasets you will unify, and how your content or CRM platform will evaluate the information for predictive purposes. For instance, you might want to use a story to maximize potential earnings from a particular product. This could involve data sets related to engagement rates, lead nurturing, landing page conversion, and so on.

The more data you feed into such a system, the more precise the predictions you’ll be able to make. AI and machine learning are enabling data scientists to apply a combination of predictive analytics and meta data management to business. This lets marketers anticipate changes in consumer behavior and the impact of macroeconomic trends on business.

2. Identify Snags in the Buyer’s Journey

Making a sale in B2B requires way more than flashy advertisements and bold promotions. The modern buyer’s journey is typically made up of three key stages: Awareness, Consideration, Decision.

buyer's journey
Credit: HubSpot.com

Ideally, each stage should work as a vector to ultimately produce sales.

While it’s easy for marketers to design content marketing strategies to play to each stage, the parts that tend to get overlooked are the transitions. In other words, how well does your content bridge the gap between one stage of the buyer’s journey and the next? This is perhaps where data provides the most valuable insights related to sales.

Funnel visualizations can reveal patterns in regard to where people drop out or delay the progression through the buyer’s journey. Using this data, businesses can refine their transitions and work to eliminate the major roadblocks. Some simple metrics to start out with are bounce rates, session duration, and conversion rates of your landing pages — all of which can be tracked via Google Analytics.

google analytics behavior flow
Credit: Google Analytics

For example, let’s say you run a SaaS company and your Awareness stage content (blog posts, e-books, podcasts, etc.) is doing a fantastic job in getting traffic to your Consideration stage content on your website, which includes landing pages to sign up for a webinar or download a white paper.

However, you notice that the bounce rate for these pages is very high (around 95%) and the time on page is only a few seconds. This is a good indicator that there is interest, but the transitions from your Awareness content aren’t giving people enough information or motivation to convert. Therefore, it might be time to re-examine content at the transition point (email invitations to the webinar that you send to people who’ve read your blog posts or subscribed to your newsletters) or add more information to your landing pages.

Keep in mind, snags in the buyer’s journey can have much deeper-rooted issues than the example above — all of which can impact your sales numbers. Understanding how your content impacts the success or failure of your customer journey will likely require a great deal of critical thinking (and digging into funnel data).

3. Use Intent Data to Constantly Refine Your Sales Model

The term “intent data” is a buzzword that has been floating around the marketing world for all of a hot second. Intent data refers to behavioral information that gauges a person’s online activity and how likely they are to take a desired action. In terms of how this relates to your content marketing and sales efforts, these insights combine both topic and contextual data.

intent data
Credit: Infer.com

Topic data refers to the level of interest someone expresses about a subject when they search for something on the web. For example, if someone Googles “how to simplify customer service,” and lands on your blog about how to program a chatbot, they are showing some degree of intent. There are generally four categories of topic data:

  1. Anonymous First-Party Behavioral — These are visitors to your website who haven’t taken any action that identifies themselves. It is possible to identify their company by their IP addresses.
  2. Known First-Party Behavioral — These are visitors to your website who have shared personal information by filling out a form.
  3. Anonymous Third-Party Behavioral — These are unknown visitors to other websites with similar content to yours. You can identify them via the topics they browse and track them via their IP addresses.
  4. Known Third-Party Behavioral — These are known visitors to other websites who’ve shared information and whose content preferences are recorded. You can then use tools to measure and capitalize on the purchase intent of a pre-segmented audience.

Now, topic data is more or less useless without the right context. Contextual data revolves around diving into the who of the person taking the action. For instance, if the visitor reading your article on chatbots is a business owner, there is a good chance the person is considering a solution for customer service needs. On the other hand, if the reader is a programmer, it’s very possible the professional is looking for information about how to build or improve a chatbot. In this way, intent data plays a key role in how you define your sales process.

Different types of web visitors will have slightly different views of the buyer’s journey in relation to your business. You need a system that gauges the intent of a visitor from how they interact with your content on various platforms; the insights you glean from this form the basis of how you craft your landing pages.

Intent data lets marketers put the right content in front of the right eyes. Start by personalizing your website to “anonymous” users. Solutions like Evergage can be synced with CRM data and use machine learning to better understand the intent of visitors. It can then draw on a wide range of behavioral insights to help you serve ultra-targeted content.

Evergage
Credit: Evergage.com

For example, the system can sort visitors by industry and automatically build segments based on key attributes. From here, you can deliver customized messaging that fits into the narrow views of each of these segments.

Next, you should base the processing of inbound leads on engagement. Ideally, this should work to quantify the visitor’s intent based on the manner in which they interact with your content. If someone is looking at your blog section, they would likely fall lower on your lead scoring model. If they are looking at pricing, they would obviously rank higher.

scoring model
Credit: Business2Community.com

Intent data should always play a key role in how you nurture leads and go about making sales.

Over to You

In many ways, the data you get from your content marketing strategy is the lifeblood of your sales efforts. As big data continues to grow at exponential rates, both in size and application, the challenge will always be using these insights to boost your bottom line.

Refining your content strategy is a task that never truly ends. As long as you keep up with what your analytics are telling you, and identify and iron out the weak spots, spikes in sales are always around the corner. Good luck!

3 Effective Bottom-of-the-Funnel Marketing Tactics for Social Media

Up to 74% of social media users have been influenced to make a purchase thanks to brand exposure. It just takes a focused approach to tap into the intricacies of the channel. This begs the question: Where do action-prompting, bottom-of-the-funnel marketing tactics fit into the complex world of social selling?

At this point, every marketer knows how important social media is for building a presence and making sales. However, marketers also know that selling products or services on social media requires a vastly different approach than “spray and pray.” This is because most people simply aren’t surfing their feeds for sales pitches (although they’ve come to expect it now); they are looking for something interesting to keep them busy — away from work.

While they certainly have their place, the flashy promotions and deals need to be placed perfectly to avoid turning people off. A study by Sprout Social found that 57% of social media users get annoyed by — and consequently unfollow — brands flooding them with promotions.

That said, up to 74% of social media users have been influenced to make a purchase thanks to brand exposure. So obviously, sales are still taking place here. It just takes a focused approach to tap into the intricacies of the channel.

This begs the question: Where do action-prompting, bottom-of-the-funnel marketing tactics fit into the complex world of social selling?

Given the massive amounts of content being published every second, expanding your reach depends heavily on your ability to position content in the right place at the right time. What you need to consider is your industry, message, location, and platform. Let’s talk about how you can get your sales content on social media without getting on your followers’ nerves.

Use Influencers and Brand Partners to Promote Coupons

Coupons have been a staple in bottom-of-the-funnel sales tactics for generations. For retail or e-commerce businesses, coupon promotion is a necessary evil. While coupons have taken a number of different forms in the digital age, the effectiveness has remained constant. A report from Valassis found that coupons influence 80% of consumers to purchase from a brand.

However, there’s no hiding from the fact that social media’s educational and informative nature is not exactly the ideal environment for coupons. Thankfully, there are a number of strategies you can use to get your promo codes and deals out there without making your page resemble an obnoxious salesperson.

Perhaps the best way to promote your coupons on social media is through extensive partnerships; especially with influencers. Keep in mind, a few coupons here and there won’t annoy most social media users — at least, not to the point of unfollowing. That said, if you have a higher number of partners/accounts to spread out your coupon campaign, you are:

  1. Reaching new audiences, and
  2. Not overburdening them with promotional jargon.

Influencers and micro-influencers can be instrumental in getting your promo codes in front of a larger, more targeted, more engaged audience. Having a micro-influencer or authority in a topic recommend a relevant product or service makes the audience more receptive toward trying it out, while building trust for the brand.

SEMrush, my former employer, recently used this strategy to great effect by getting dozens of digital marketing experts to spread the word about its first-ever conference in India, using personalized coupon codes:

Credit: Twitter

When you are looking for influencers or brand partners to promote your coupons, you need to look for relevancy and content overlap. The key here is not to go overboard. For instance, let’s say you have two coupon codes you are looking to promote on social media. If you have six partners, you could have three of them promote one of the coupons and the other three do the same the following week, with a total of 12 posts over two weeks — a number that likely won’t irk followers.

Pushing coupons on social media is a task where you want to tread lightly. Using a “proxy mouth” to spread the word is a fantastic way to draw attention, without agitating users.

Use Chatbots to Move Prospects Through the Buyer’s Journey

Chatbots are one of the most interesting (and widely debated) developments to emerge in social media in the past few years. Essentially, these are AI-powered tools that can be programmed to provide instantaneous, pre-fed or learned responses to customers and prospects.

The machine learning (ML) and natural language processing (NLP) capabilities can spot the patterns in customer interactions and adjust accordingly. While many brands use these bots to handle common customer service inquiries on their Facebook pages around the clock, some use them to take and process orders.

In fact, research by HubSpot indicates that nearly 50% of consumers would buy a product from a chatbot. So, while bottom-of-the-funnel content may have a limited place on your public page, it could be extremely useful if programmed into a bot.

ManyChat is one of the of the most user-friendly Facebook Messenger chatbot tools. It requires zero coding skills and uses NLP to understand certain phrases and preferred responses. In terms of refinement, the program lets you split test certain responses to optimize your sales tactics.

Credit: ManyChat.com

Further, you could set up the bot to make upsells and cross-sells. However, creating a chatbot to do this seamlessly is no simple task. At the end of the day, robots cannot replace humans for all tasks (at least, not yet). Programming a chatbot to nurture leads and create revenue requires frequent analysis and refinement; especially when it has to be made to understand and use language. Keep in mind, this technology is still very much in the infancy stage.

Social listening and monitoring tools can be of great help here. You can use them to generate vast datasets from social networks like Facebook, Twitter, and YouTube, and more for market research, analyzing user sentiment, targeting segmented audiences with personalized content, and generating sales leads.

For example, NLP processing would look for terms like “hate,” “love,” “favorite,” etc. Some of the more advanced tools are designed to recognize slang terms to differentiate the meaning of certain sentences such as, “That video made me sick!” from similar-sounding ones like “That video was sick!”

Chatbots are fantastic for creating real and personalized sales experiences, without an expensive-to-maintain team. Used in conjunction with other platform-specific social media automation tools for building fan followings, content creation, scheduling, and engagement, a chatbot can potentially be your most powerful sales weapon on social media.

Use Videos as Calls-to-Action

It’s no secret that the essence of social media is shifting toward video. The major networks are slowly but surely becoming channels centered around video content. The big Facebook algorithm update in 2018 essentially proved this.

Video now holds a great deal of weight, in terms of how content is placed on people’s feeds. There are many ways you can go about maneuvering your bottom-of-the-funnel sales content to play to this concept. Creating product demonstrations to highlight the best features is one of the most effective and proven ways to go about this. For example, Blendtec runs a series of videos titled “Will it Blend?” in which they famously blended an iPhone X.

They have also blended things like marbles, rake handles, Justin Bieber’s biography, and more. All of these episodes are shown on the “Will it Blend?” Facebook page. The beauty of these videos is they promote the blender, while displaying its capabilities in a comical way. So, it never really feels promotional or bottom-of-the-funnel-esque.

The major social networks have made one thing blatantly clear: Produce video content, or be left behind.

Now, if you don’t have much experience producing video content, it might take a while to find the groove, depending on your product or service. The most important part is that each has a clear call-to-action that prompts sales. For example, at the end of the video, you can talk about special deals or time sensitive offers to get people to take an action toward purchase as soon as they finish watching the video. Or, you can bundle it up with live streaming, with subtle sales pitches built in.

Over to You

Social media, in general, is at a transitional point in its short existence. It has morphed from a tool to connect with friends and family to a powerful engine that influences people’s mindsets.

Simply put, pure sales-oriented content will not do well on social media, unless it is optimized for engagement. Further, you’ll constantly need to analyze your campaigns and the reactions of your audience. If you misread them and promote your BOFU content too hard, they’ll ditch your brand without a second thought.

4 Ways Artificial Intelligence Can Impact Your Conversion Rates

At this point, there is little doubt that artificial intelligence is the future of business. The Salesforce “State of Marketing” report found that more than a fifth of businesses currently use AI for marketing purposes, including programmatic buying, personalization, and real-time offers.

At this point, there is little doubt that artificial intelligence is the future of business. The Salesforce “State of Marketing” report found that more than a fifth of businesses currently use AI for marketing purposes, including programmatic buying, personalization, and real-time offers.

artificial intelligence graphic
Credit: Salesforce

Further, AI is the fastest-growing sales technology, according to the Salesforce “State of Sales” report.

Outside of sales and marketing, companies are frequently using artificial business intelligence for tasks like reporting, dashboards, and data warehousing and analytics.

While applying AI to these business operations is certainly beneficial, it does beg the question of how exactly this technology will impact the future of conversion optimization, as well as the most important person in a business: the customer.

At the end of the day, the thing that really matters in business is the numbers. AI technology for analyst reports and predicting turns in the market is all well and good, but if it isn’t boosting sales, then what is the point?

The good news is that AI is showing promising results in terms of conversion rates, proving once again that big data is paving the way to a more profitable future for many companies. Here’s how.

1. Enriches Customer Experience

The concept of improving the customer experience (CX) is a big challenge for many reasons. CX is not merely limited to the user-friendliness of a website or the customer service that is provided; it is a combination of all of these elements. Yet another report from Salesforce found that consistency is a core element in a positive customer experience, and 70% of customers say connected processes based on earlier interactions and contextualized engagement are important for them to do business with a company.

This means that in order to improve the CX for customers, brands must adjust every part of the experience to create a coherent message.

Studies have found that customers are willing to pay more for a better experience with a business. It also has a strong effect on their likelihood to repurchase and refer the product or company to friends.

artificial intelligence graph
Credit: Temkin Group

But what exactly makes up “customer experience” and where does AI fit in?

CX is essentially the accumulation of every interaction a customer has with a business, from introduction, to purchase, to customer service. As experienced business owners know, one small kink in the journey can send people running. AI and machine learning technology can help create a more optimized experience for each customer, from start to finish.

For example, when fashion brand FlyPolar experienced a near 400% decrease in sales in the span of just four months, the business executives knew that something wasn’t right. Because most of its customers purchased online, FlyPolar used AI software to optimize its website landing pages. By using machine learning technology, this AI program “learned” which designs performed best and delivered positive results.

After several weeks of testing, the AI system identified the core roots of the conversion problems and provided the proper insights for solutions. FlyPolar created a simpler four-step conversion funnel on its website, with optimized CTA button placement throughout the landing pages. By using machine learning algorithms, FlyPolar increased its checkout page traffic by 16% and its order value by 13% in just three weeks.

This case study shows that AI technology can quickly and easily identify the root of the problem, arguably one of the most difficult parts of optimizing the CX.

The prediction capabilities of AI-powered systems can also make it easier for your customers to find exactly what they are looking for; which, in turn, improves their experience with your website. Traditional searches base results on matching keywords or similar phrases, which may or may not be accurate. In contrast, present-day search programs use ML to “learn” consumer behavior and accurately return the items that match their queries, based on their previous behavior.

ML-based search takes numerous data points into consideration, including past view and click rates, ratings, and even inventory levels to provide customers with appropriate and targeted results.

It should be no surprise here that Amazon is one of the leading retailers to utilize this kind of technology. Amazon’s recommendation engine uses item-to-item collaborative filtering to provide search results that are based on multiple data points, rather than just keyword matches. Not only does the algorithm take each customer’s past searches, purchases, and product views into consideration, but also the ratings and popularity of each item.

artificial intelligence example
Credit: Amazon

Since Amazon debuted an AI-based recommendation engine, its profits started growing exponentially. By basing search results on multiple criteria, Amazon is able to push certain products while providing shoppers with the results that fit their needs, providing a better experience for the customer with each query.

2. Enhances Personalization

Buying online is no longer a one-size-fits-all experience. In fact, customers are becoming more and more unyielding that businesses customize just about everything to fit their needs. According to Accenture’s “Personalization Pulse Check” report, three out of four customers report that they would be more likely to purchase from a brand that offers personalization and recognition than businesses that do not.

Personalization is also directly related to higher profits. Researchers have found that businesses utilizing big data systems to create personalized experiences for their customers report up to 10% higher revenues.

AI is able to take the guesswork out of personalization. One of the best examples of this strategy in action comes from Starbucks, which reported a 300% increase in customer spending thanks to its highly-customized marketing program. Customers regularly receive personalized offers and incentives to earn more points toward a free drink reward. Every customer’s offer is based on past behavior, including how often each customer purchases and which types of items the customer tends to buy.

Starbucks’ AI-powered personalization system sends out around 400,000 variants of emails with incentives that are almost entirely unique for each recipient. Due to the hyper-personalization that Starbucks offers, many customers find it easy to fulfill the requirements for these rewards. This does wonders to increase consumer participation, purchase frequency, and ultimately, customer loyalty.

artificial intelligence in loyalty programs
Credit: Starbucks App

Of course, loads of consumer data are needed in order for online companies to provide this high level of personalization. Each customer’s preferences, demographics, and behavior must be tracked and analyzed in order for brands to properly adjust their strategies to fit an individual consumer.

The results from integrating personalized messaging and marketing speak for themselves: 63% of marketers report that an increase in conversion rates was the top benefit they saw from personalization.

AI-powered personalization can be used to help customers move their way through the buyer’s journey, as well. Using ML, these programs use predictive analysis to incentivize shoppers with personalized messages, email campaigns, retargeted ads, and more.

The algorithms can study consumer behavior so that ads and other messages are sent at the right time and trigger the ideal response. For example, an algorithm that tracks customers’ click rates and scrolling habits can predict when new customers are likely to abandon their carts and send a well-timed message or personal offer to keep them engaged.

artificial intelligence-generated offer
Credit: Acquisio.com

3. Improves Results of A/B Testing

Most marketing teams and web designers rely on A/B testing to determine the best layouts, color schemes, and messaging to grab their customers’ attention. However, there are obvious limits to the “old-fashioned” testing approach. Gathering the research takes time, and there is not always a clear winner from the results.

In fact, the traditional form of this strategy may not even be effective. Jeremy Miller, marketing director at Sentient, said during an interview:

In traditional A/B testing formats, you have your control vs. an experiment. You run that experiment against your traffic, and whichever design performs better is the one you deploy … but people have found that six out of seven experiments don’t result in a positive outcome, so you actually have to put a lot of energy and resources to try to determine how you can actually increase conversions using A/B testing.”

AI can solve the three biggest problems with traditional A/B testing: time required, insight, and limited variables. By reducing these weaknesses, marketing teams have the ability to make informed design changes with the results and data to support them. Instead of taking a linear approach to testing, AI can compare thousands of variables at the same time and instantly compare the results to determine the best combination.

For example, online lingerie company Cosabella used an AI-driven testing approach when it was redesigning its website. Rather than comparing designs two at a time, like a traditional A/B test would, Cosabella was able to carry out an A/B/n experiment with 160 different design elements, simultaneously. With that many variables, it would have taken up to a year of A/B testing to gather results; with AI, the process took only seven weeks.

artificial intelligence testing
Credit: Cosabella.com

Through this testing process, Cosabella was able to determine the aesthetics that resulted in better conversions. It found that customers bought more when CTA buttons were pink, rather than black. The company also determined that family values resonated with its customers, so it did away with “free shipping” banners and replaced them with “Family Owned Since 1983.” After these short seven weeks of testing, Cosabella reported a 38% increase in conversions and a 1,000% lift in newsletter signups.

4. Speeds Up Customer Service

The faster a company can respond to customer inquiries or issues, the better. For this reason, the demand for live chat grew by 8.29% last year. Unfortunately, most businesses do not have the resources to keep their customer service departments running 24/7, leading to long response wait times for disgruntled customers.

By automating customer service with AI-powered chatbots, businesses can not only solve the issue of wait time, but also the quality of the response and assistance that customers receive.

In 2012, Amtrak’s customer service department serviced 30 million passengers each day. Obviously, with such high numbers, it was difficult to handle individual inquiries in a timely manner, so Amtrak decided to jump on the chatbot train with its AI-powered customer service rep “Julie.”

Julie was able to resolve most of these issues by pre-filling forms through scheduling tools and guiding customers step-by-step through the online booking process. Because most of these problems were handled online, the number of calls and emails decreased dramatically. At the end of the first year, Julie had answered over 5 million questions, increased booking rates by 25%, and generated 30% more revenue, thanks to upsell options included in the messaging.

artificial intelligence chat
Credit: NextIT.com

In terms of conversions, live chatbots can not only resolve issues in an instant, they can increase the chances that a customer decides to buy. When a customer’s issue is solved quickly, they are twice as likely to repurchase from that brand. Live chat is also the preferred method of communication for resolving problems or issues; however, it is important to note that the quality of the messaging far outweighs the speed of the response.

According to Kayako’s report on live chat service, 95% of customers say that receiving a thorough response that answers their question or resolves the problem is more important than just getting a quick reply. This is a major issue that many companies have with AI chatbots; they are simply programmed to give automated, scripted responses, which 29% of customers report as simply frustrating and unhelpful.

This is where AI-based chatbots save the day; they can adjust their messaging based on FAQs, as well as the customer’s phrasing and responses. This process leads to better and more natural replies from bots that delight customers and give them the timely information they need.

An AI chatbot is not a one-time fix to the issue of customer service. It is a strategy that must be properly monitored, adjusted, and perfected over time in order to deliver the best results.

The Wrap

Many conversations these days are revolving around AI and its impact on the future of business. And, quite honestly, it seems like the answer to just about every current business planning issue out there. Predictive analytics can tell you when things are about to change. Machine learning can understand your customers on a personal, granular level, and big data can keep track of every metric for accurate reporting.

However, one of the clearest benefits of AI is the direct impact it can have on conversions. It eliminates the guesswork from improving the CX of webpages and delivers timely and accurate testing results needed to increase the likeliness of conversions. Big data systems and AI make hyper-personalization possible to customize the experience for each visitor. Finally, chatbots can use ML to instantly engage with customers, resolve issues immediately, and close sales.

Success all boils down to how a business makes the customer feel. Most of the time, this is what determines whether or not a customer will purchase. Studies have found, unsurprisingly, that when customers feel special, important, and satisfied, they are more likely to buy from those brands. AI gives brands the power to do just that.

How to Use Sentiment Analysis to Transform Your Digital Marketing Strategy

The goal of sentiment analysis is to increase customer acquisition, retention, and satisfaction. Moreover, it helps put the right brand messaging in front of the most interested eyes.

Sentiment analysis is a fascinating concept.

Brands use it to better understand customer reactions, behaviors, and opinions toward their products, services, reputation, and more. The goal of sentiment analysis is to increase customer acquisition, retention, and satisfaction. Moreover, it helps put the right brand messaging in front of the most interested eyes.

Before the digital age, gauging and understanding sentiment was an incredibly cumbersome process. It typically involved sending out surveys manually, going to the streets and asking people, or gathering focus groups in one place at one time. The big data-infused model of sentiment analysis we know today hit its stride on the political scene in 2010. Since then, it has morphed into a key tactic in marketing plans. These days, most of the grunt work is automated.

However, even with all of the advances in areas like martech, voice search, conversational commerce on social media, virtual assistants, and big data analytics, understanding how to actually use sentiment analysis to improve the bottom line is a complicated task.

Here are a few key approaches to help you get the value you need.

Know the Terms and Phrases That Indicate Intent

Most businesses today (hopefully) don’t even begin their digital branding and marketing efforts without a list of keywords relevant to their industry and a plan on how to target their audiences. You should have a good idea of the terms and variations that bring you traffic to your website, when used in conjunction with your brand and products. If you run an auto repair shop, people are likely finding you on the web through terms such as: body shop near me, auto repair, replace brake pads, etc.

Google Search Console gives you a great, fairly accurate idea of what’s bringing people to your website:

google search console
Credit: Author’s own

In terms of sentiment analysis, to gain actionable insight, you need to know how people are using these keywords in a way that indicates interest and engagement potential. Now, this is perhaps the biggest gray area in sentiment analysis, because not all positive sentiment equates to sales. Just because there are a lot of positive words around luxury cars doesn’t necessarily mean people are about to buy.

However, there are certain terms and phrases that signal people have entered your buyer’s journey. Let’s say you run an SEO agency and one of the terms you’re tracking for sentiment analysis is “Google update.” If you notice that a lot of people are searching for things like “what to do after a google algorithm update?” or “how to recover from a google penalty?” it’s a good indicator that they might need your services at the moment; you should target them accordingly.

Spot Patterns in Product Reviews

At its core, sentiment analysis is a game of pinpointing patterns and reading between the lines. Simply put, the more genuine and meaningful feedback you get on your product, the better insights you will gain into your customers.

Of course, gathering such high-quality feedback is easier planned than executed; especially for newer or smaller companies. Only 10% of customers will review or rate a business after a purchase, while half of consumers will leave a review only some of the time. However, the number of reviews jump significantly to 68% when a company asks the customer directly to leave one.

In order to find fruitful, up-to-date patterns, you need to make it a marketing process to consistently seek out new reviews. Then, you’ll want to start by searching for common adjectives. These should include words like:

  • great, simple, easy,
  • or awful, difficult, poor, etc.
trustpilot review
Credit: Capterra.com

In the above image, there are a good amount of reviews that include the word “great” for this product. Looking at the context around this term, we notice recurring patterns around components, like features and usability, and “not so” great opinions on customer service.

Finding recurring themes in customer sentiment will give you a better picture into the positive and negative aspects of your business or product. These can indicate the level of trust people have in your brand and how likely they are to give you a recommendation. When you are looking for patterns, try to come up with several adjectives that shed light on both sides of the spectrum.

  • What words are commonly used to describe their experience?
  • Is there an issue that forces multiple people to leave negative reviews?
  • What part delights them the most?
  • What’s preventing you from solving common problems?
  • Which products or solutions are users comparing yours to?

The answers to these important questions can help you understand user sentiment better and build a customer-focused marketing strategy.

Look to Social Media for Unabashed (Unfiltered) Opinions

Oftentimes, social media is one of the best places to get raw opinions, where people don’t hold back —  both in positive and negative lights. Knowing how people feel in an unfiltered environment can be a great way to tell which parts of your business are working very well —  and not so well.

A social listening platform is an important tool to keep in your portfolio for monitoring online mentions and gathering important datasets. Tools like Mention, Talkwalker, and Brand24, not only keep an ear on social mentions, but also turn these comments and hashtags into valuable customer analytics to help your marketing team understand your customers even better.

For instance, the online gaming developer Wargaming used brand monitoring techniques to analyze its customer’s desires and see which products performed best. The company tracked its users’ social media conversations to see what they were looking for, what parts of the games they liked or disliked, and any suggestions they offered for improvements.

Similarly, you can use a social listening tool to combine all your brand mentions into one database, giving your marketing team a bird’s eye view of audience sentiment on social platforms and identify areas to work on.

talkwalker
Credit: Talkwalker.com

While gathering this sentiment is good, the most important thing is knowing what to do with it. About 83% of customers who make a social mention of a brand —  specifically, a negative one —  expect a response within a day, and 18% want one immediately. Unfortunately, a majority of these mentions go unanswered, which can really impact a brand’s image. By utilizing an effective real-time social listening program, you can not only stay on top of social buzz, you can intervene and reply to any negative sentiment right away.

Some of the next steps will be fairly obvious, especially when you’re dealing with negative feedback. For instance, if your customer sentiment from social listening reveals that people are having trouble updating their software or there are issues with the product itself, this indicates that some redesign is necessary. However, don’t get too comfortable when you are getting positive reactions —  these tend to trick companies into thinking that no improvements are needed.

This kind of feedback can support a stronger marketing strategy. Let’s say your business sells pool supplies. While your customers may not be tweeting about your great chlorine chemicals, they are more likely talking about the fun pool floaties and games your website sells. Therefore, it would be helpful to highlight these fun accessories, as well, by listing them more prominently on your page and even including UGC to promote them.

poolfloatz
Credit: Instagram

Use Predictive Analysis to Spot Trends and Automate Actions

Now that you have all these valuable insights, you need to know how you can use them to shape your current and future business strategies.

Plugging your sentiment analysis into a predictive model is crucial for spotting trends, getting a feel for how opinions are progressing, and determining your next steps. Predictive analytics use machine learning and AI technology to not only gather, but analyze loads of consumer data and make accurate projections. These systems gauge historical behavioral data to help determine the best plan of action in the future.

In fact, customer segmentation and targeting (which is the logical next step after you analyze your audience’s sentiments) is one of the areas where applying AI and predictive analytics has the highest chance of working well for business.

applications of AI
Credit: Emerj.com

In order to develop an optimal predictive model for sentiment analysis, ask yourself:

  • What do you want to know?
  • What is the expected outcome? What do you think your customers are thinking?
  • What actions will you take to improve overall sentiment when you get the answers? How will you automate these actions?
  • What are the success metrics for these actions?

The Wrap

Chances are, your customers are already telling you what you need to make improvements to your business. By gathering as much data as possible on customer sentiment, your marketing team can understand just what needs to be done to provide a better experience, tweak campaigns accordingly, and acquire and retain more customers in the process.

Be sure you know what to data to collect, how to mine it, and how to apply it to keep raking in the revenue.

The 1-2-3 Guide to Ace Mobile App User Acquisition

Acquiring users for your native mobile app isn’t a new challenge, but it keeps getting harder. The number of apps on the market keeps on rising, and competition in every app sector keeps increasing.

Acquiring users for your native mobile app isn’t a new challenge, but it keeps getting harder. The number of apps on the market keeps on rising, and competition in every app sector keeps increasing.

Last year, over 6,000 apps were released every day on average in the Google Play store alone.

App marketers are working in a saturated market, competing for a limited number of users, who are becoming more discerning when it comes to the apps they install and use.

Without an enormous budget, there’s no choice but to get creative with user acquisition if you want your app to get you any meaningful usage among your customers. It’s time to master some new tactics in order to make sure your app remains a center of growth for your business, while keeping your cost per acquisition (CPA) in check.

1. Get Creative With ASO

App Store Optimization (ASO) remains a key pillar of any good user acquisition program. Careful use of keywords is still crucial to get your app to rank highly in app store searches and on app charts, with 65% of downloads on the iOS app store still coming through organic search, as per App Annie’s “State of Mobile in 2019” report.

App marketers continue to use updates to the app’s name, description, and icon as their go-to methods for improving ASO, although updates to app name and description dropped slightly in 2018.

app user acquisition chart
Credit: AppAnnie.com

However, ASO tactics have evolved and improved. Working ASO to the max in 2019 means using seasonal keywords, images, and branding to take advantage of yearly events, like winter holiday sales; whether it’s something geography- or culture-focused like Singles Day, or a global shopping hype machine like Black Friday.

App marketers are also seizing the opportunity to use tentpole marketing to adapt ASO to sporting or cultural events, like the Super Bowl or the Oscars, as a way of attracting more users. High-profile feature launches are another window for ASO updates that bump your app’s visibility in app stores. For example, Progressive Insurance created a game called Super Duper Bingo, created from ads of the previous years and marketing clichés to air during the 2016 Super Bowl.

app user acquisition example
Credit: Brandchannel.com

What’s more, today’s app marketers also update screenshots and videos on a regular basis, in order to keep app branding consistent across all touchpoints. For iOS apps, updates to keyword banks and promotional text copy also provide important potential for ASO.

2. Make Mobile Affiliate Marketing Measurable

Affiliate marketing may have a bad reputation in some circles, but it’s going through a rebirth for app marketers.

Some marketers are starting to approach affiliate marketing as they would any other type of performance marketing, by vigilantly measuring conversion lift using more sophisticated attribution solutions.

With smarter measurement in place and less risk of fraud, marketers can allow influential affiliates to promote their products with social media posts, native paid advertising, and sponsored on-site content, as well as traditional affiliate marketing ads and UTM-enabled links.

The more holistic approach to affiliate marketing channels leads through a trackable and measurable process that makes it easier to optimize each stage of the user journey. Because you only pay after a lead has converted, affiliate marketing is a great way to keep your CPA down and improve ROI.

Succeeding at affiliate marketing for increasing app users requires plenty of research into finding the right third-party partners to help extend your reach to new audiences. You’ll also need to tread the fine line between developing an attractive affiliate program, with healthy commissions and low barriers to entry, and keeping it cost-effective so that you aren’t paying over the odds for each lead.

3. Drive Revenue With Retargeting Ads

App retargeting ads are still among the most effective ways to drive conversions and revenue uplift. Over the last two years, one out of every four conversions was enabled by retargeting programs, and apps running retargeting ads enjoyed nearly 50% more revenue uplift over those that did not. That’s according to a recent study from mobile attribution analytics company AppsFlyer, based on its analysis of 4.5 billion retargeting conversions.

app user acquisition graph
Credit: AppsFlyer

 

Thanks to the availability of more sophisticated retargeting engines from the various ad networks, app marketers are better able to identify and build ad targeting audiences of potential users who have shown interest in the app, but failed to convert to paying users.

These are prime leads for retargeting ads that remind people about the benefits of the app and convince them to return, to upgrade to a paid license, or to make in-app purchases.

New segmentation tools also allow marketers to develop focused retargeting ads that are shown only to those leads who are likely to deliver the highest revenue, improving ROI. This should be combined with advanced personalization techniques, drawing on your existing data on lead behavior and interests to make retargeting ads more relevant and more effective.

4. Get All the Reviews You Can

The importance of reviews is old news for app marketers, but many still seem to overlook just how significant reviews and ratings can be. About 95% of people read app reviews, and 80% say they trust them, per a BrightLocal survey, making app reviews highly influential for success in acquiring users.

Many app marketers focus on app reviews on third-party sites, and fail to bring in enough reviews on the app site itself. After the app store, the most likely place that potential users will look for reviews is your app download page. Plenty of app reviews and a high customer satisfaction ranking impacts on your app’s overall scores for ASO, significantly improving download and installation rates.

Frequently, marketers who bring in user reviews don’t gather enough of them. Your app needs around 60 reviews to get an average rating, and around 150 reviews to be ranked as one of the top apps in the app store. So it’s imperative to constantly find new ways to bump up the number of your reviews.

app user acquisition example two
Credit: MobileAppDaily.com

And don’t forget that your reviews need to be authentic to potential users. If you have dozens of reviews that are all positive and uncritical, visitors will dismiss many of them as fake and won’t take them seriously. So resist any temptation to pay for positive reviews or to make them up yourself.

Combine Multiple Tactics

App user acquisition isn’t easy — and it can be very expensive — but using the right tactics can help you get more downloads, installs, and in-app time without spending a fortune. Retargeting ads for interested leads who haven’t yet converted, fine-tuning your ASO in creative ways, gathering enough authentic reviews, and advancing affiliate marketing networks are all critical pillars of a successful user acquisition campaign.

By mixing and matching these smart tactics, you’ll be able to create an app user funnel with multiple entry points that keeps your app profitable.

4 Mistakes Multichannel Marketers Make and Lose Customers

Most businesses today understand the importance of multichannel marketing. They invest in SEO, PPC, social media, and even trade shows and conferences. However, if your hard-fought marketing budget is not able to increase your customer base or pool of prospects consistently, then you can be sure your funnel has developed a few holes in the wrong places.

Most businesses today understand the importance of multichannel marketing. They invest in SEO, PPC, social media, and even trade shows and conferences. However, if your hard-fought marketing budget is not able to increase your customer base or pool of prospects consistently, then you can be sure your funnel has developed a few holes in the wrong places.

Unfortunately, both B2B and B2C businesses are guilty of making sales-killing mistakes again and again; oftentimes, putting off customers without realizing it. These simple blunders could cost your business big-time, hurting growth opportunities and diminishing returns from existing customers.

Here are four pitfalls you should be wary of while implementing an integrated, omnichannel marketing strategy, so that you don’t lose any targeting opportunities. All of these tips apply to the technology, methods, and tactics that are currently used by entrepreneurs, companies, and marketers, cutting across industries and geographies.

Preferring Safe Over Sorry

Taking risks is a big part of running a business, and something that many entrepreneurs are used to. However, once they start experiencing success and growth, many begin to shy away from taking chances.

In the long run, many business owners admit that playing it safe was one of their biggest mistakes. In terms of marketing and sales, going the safe route can actually hurt your brand. Why? Because it is simply boring.

According to a study by Adobe, 54% of marketing experts know that they should be taking more risks, and an alarming 82% of companies believe that they need to reinvent their branding in order to succeed. Remember, your customers’ needs and mindsets are constantly changing. If you rely on the same tactics, the same advertisements, and the same marketing messages, people will eventually get bored and your results will diminish.

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Credit: Adobe on SlideShare.com

Reassess the methods and tools you use for audience analysis, and take a look at how the demographics have shifted over the years. Compare your past results with your current numbers to see if there are any noticeable differences. It may be time to take some risks, try something new, and see what happens.

Relying on Imperfect Bots

Saving on customer support by passing on the majority of your customer service workload to an automated chatbot system sounds like a dream come true. If used correctly, these bots answer customer inquiries, resolve issues, and even make sales. This is why the AI-powered chatbot has exploded in recent years, with 15% of consumers reporting that they have used one to communicate with businesses over the past year, according to Drift’s 2018 “State of Chatbots” report. (Opens as a PDF)

However, just because this customer service channel may be working for some businesses, it does not mean that it is a one-size-fits-all solution. When creating a chatbot, the overarching goal is to solve the cognitive puzzle that fills in the gaps between a bot conversation and a human conversation. When a conversation is initiated, in any capacity, there is an exchange of data that sheds light on emotional engagement between the two parties. Take away the emotional exchange, and empathy is unachievable.

Programming an online bot to handle all sorts of customer queries and interpret exactly what someone is looking for does require a bit of technical knowledge and understanding, despite what off-the-shelf chatbot sellers will have you believe. A poorly programmed chatbot could easily result in lost revenue.

Just one bad or frustrating experience with a chatbot will likely push away 73% of customers forever. If a bot is simply not answering their question or simply offering irrelevant information, then it is doing your business far more harm than good.

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Credit: SherpaDesk.com

In order to determine whether or not your chatbots could use some help, take a look at some important metrics. Has your sales cycle lengthened? Are fewer leads moving down the buyer’s funnel? Are you facing an increase in helpdesk escalations, despite an improvement in response times? An effective sales bot should be boosting conversions — or at least micro-conversions — so if numbers are shrinking, that’s a definite red flag.

You can also try adding a short satisfaction survey at the end of each chatbot conversation to gather some customer feedback and help identify any weak points that are killing the customer experience.

Ignoring the Micro-Influencer

It seems like everyone and their grandmother is “leveraging” influencer marketing these days, trying to reach the promised (read, purported) 11-times ROI of other digital marketing methods. It is easy to get blinded by the numbers; especially in terms of “reach” and “engagement.” Just because an influencer has a huge following doesn’t necessarily mean that their promotion will help your business.

Micro-influencers (accounts with 100,000 followers or fewer) actually perform better, in terms of audience engagement and actual “influence” — purchase rates. In fact, these smaller accounts generate over six times more engagement than influencers with massive followings. Customers are also more likely to buy a product that is recommended by a micro-influencer than they are to purchase something recommended by a person they know. Additionally, the cost per lead and cost per acquisition is lower than paid ads and regular influencer marketing.

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Credit: Mavrck.com

If your brand has dabbled with big-name influencers in the past, it may be time to consider a partnership with a micro-influencer to reach more relevant audiences. Because these accounts have smaller followings, they tend to be niche-focused, meaning that their content is highly pertinent to their audience’s needs and interests.

Obsessing Over Any One Stage of the Sales Funnel

Marketers love to talk about the importance of the sales funnel and creating marketing plans designed to “nudge” customers through it. While the sales funnel is definitely a great blueprint to guide your strategies, getting caught up in any one phase could spell disaster for conversions.

Remember, every visitor, prospect, lead, or target must go through several steps, go back, forward, and run around in circles before they become a full-fledged customer. They must be introduced to your brand during the awareness stage, learn more about your business and products during the interaction phase, get interested and place their trust in you, and ultimately make and stick to a decision to buy from you.

However, many marketing teams tend to forget this trajectory and get caught up in either building brand awareness so potential customers grow bored, or spend too much time promoting sales jargon that people totally disengage, due to advertising fatigue. If your customers are unfamiliar with your business (thanks to a lack of top-of-the-funnel marketing), the pressure to “Buy Now” will be ineffective.

Keep in mind, it might take up to 13 interactions with a brand before a lead can even be classified as a sales-qualified lead (SQL). Focusing on any one section of the sales journey can narrow the funnel significantly, meaning that fewer people flow through.

Focus a good chunk of your efforts on educating and raising brand awareness. Once people start tuning in, give them more specific information about your content and everything you offer. As you gain serious interest, then it’s time to start talking about price points, deals, and how potential customers can take proper action.

Most importantly, you need to place emphasis on the transitions between stages. They need to be smooth and organic if you want your sales funnel to function properly.

Fix Your Strategy, Fix Your Sales

Selling is an art form that no one has truly perfected. There are so many ins and outs, little details, and psychological factors that play into it — making it a deeply complex and ever-evolving practice. Online sales add another layer of complication by removing that up-close and personal factor. However, once you’ve plugged the leaks in your sales funnel, you’ll see a larger number of customers coming in and coming back. Good luck!

3 Sustainable Ways to Build a Customer-Focused Content Strategy

Learn how to create a branded content strategy that not only produces quality content, but also takes into account what your customers really want.

We’ve all seen umpteen studies proving (correlating) that the more content you publish on your blog, the more visits and leads you get. Marketers take this finding at face value and race to publish more (and more visible) content, with “experts” and “thought leaders” spewing advice on the latest tools and technology that will purportedly have your audience consuming your brand content with tears in their eyes.

The result is that every day, over 3 million blog posts are published, not to mention the countless social media updates posted. While there’s a lot of well-researched content in this haystack, much of it is conjecture and outright replication.

In order to stand out from the overflowing stream of new content, marketing teams often fall into the trap of chasing every tactic that comes their way or “borrowing” from the content created by famous brands or industry experts, and “adapting” (read, rehashing) it to fit their own content strategy. Instead, they should be gleaning lessons from big brands’ innovative content strategies and keep looking for ideas — from the most commonplace to the most implausible sources.

Let’s discuss a few ideas to ensure your content strategy never goes out of style, while matching the pace of your content production with your audience’s propensity to consume it.

Collate Industry Data and Visualize It

From a used car salesman to an apparel website, everyone has to resort to statistics and facts once a while. This was earlier done with presentations, charts, and tables. However, we’ve long needed respite from these boring and confusing ways to present numerical data.

Thanks to Edward Tufte and his four classic books on data visualization, data and visualization came together like two long-lost brothers uniting after a long time. Tufte had faced many problems in his career, because of poor data representation tools. So he revamped data presentation by adding images to data. The New York Times called him the “Leonardo da Vinci of data” while Business Insider referred to him as the “Galileo of graphics.”

Interestingly, research by Nielsen concluded that readers will pay closer attention to relevant pictures included on the page, as our eyes are naturally drawn to images. However, they will ignore visuals included just for the sake of imagery.

But it wasn’t until the availability of infographic-making tools that this method became mainstream. Today, visualization is the basis of content marketing, and not going away any time soon. Whether it is social media posts or blog articles, the simplest way to catch your customer’s eye is with pictures and videos, which get far more engagement than text-heavy content. This holds true across all digital and traditional platforms and channels.

A survey by Venngage built upon this, with empirical evidence that engagement depends on the type of visuals used in the content. Infographics and original illustrations perform the best, followed by charts and video. “Trendy” formats, stock photos, and memes actually receive the lowest amount of engagement.

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Credit: Venngage.com

The lesson here is that numbers are boring, but you can’t avoid them forever. Content marketers must take a cue from Edward Tufte’s data visualization strategy and revamp their content to include lots of graphics — even better if they are animated or interactive.

Share Success Stories

The best lessons are learned from other people’s experiences. Strangely, many marketers ignore this fact, even though every customer knows it.

Very few companies package their successes into case studies that they can easily use to appeal to a wider audience and acquire more customers.

Don’t make this mistake. Always be on the lookout for case studies — they don’t necessarily need to be yours, if you don’t have enough or relevant experience. Analyze industry examples thoroughly to gauge your potential customers’ intent, challenges in targeting them or doing business, and how these challenges can be overcome. Don’t frown upon any content format — be they detailed whitepapers, listicles, or good old FAQs. Make sure your content marketing plan provides solutions to all of your customers’ woes with actionable advice.

E-commerce platform BigCommerce has dedicated a whole section of its website to showcasing retailers’ (in both the enterprise and SMB sectors) success stories, as well as case studies. The best of the best get their own feature pages, but the showcasing doesn’t end there. (Hey, this is the best in digital merchandising we’re talking about!) BigCommerce even hands out its own annual awards to the merchants who provide a great user experience and innovative eecommerce solutions to their customers.

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Credit: BigCommerce.com

These case studies are sorted by industry or topic, and include advice on entrepreneurship, retailing, advertising, media, and pretty much anything related to doing business online. This content has no obvious CTA or tangible conversion value that you might expect. But, despite that, it is worth its weight in gold, due to the brand credibility it portrays and information it delivers to the audience.

Just as in B2C, 65% of B2B marketers believe in the effectiveness of case studies as a content marketing tactic (after in-person events and webinars). People trust real examples more than branded content. Most people (and by extension, organizations) will look at what others are doing and how they are doing it before they make a final decision. Use this psychological tendency as a base on which to build heaps of helpful content.

Combine your case studies with visual testimonials to drive home the value of your product. Video is a great way to deliver a memorable message about the joy your product brings to the lives of real users, while demonstrating to others how it can help them make pressing problems go away. Video conferencing tool Zoom used this strategy to feature one of its largest clients, Zendesk:

Instead of using a quote from the top management, like most testimonials do, this clip features sound bites from people across the organization. It shows the product in actual use by people in different roles and how every one of them is happy to do so.

Focus on Educational Content

CMI’s “Content Marketing Benchmarks” report for 2019 revealed that 77% of the most successful B2B content marketers nurture their audiences with educational content. An overwhelming 96% believe that that building trust and credibility is what qualifies them as thought leaders in their industry. Therefore, delivering useful information to your audience, leads, and customers is easily one of the most effective ways to succeed with content.

Google Analytics is so ubiquitous with website analytics that you’d think it didn’t have to care about acquiring or retaining customers. After all, we all live and swear by GA, right? But Google does not take its position as the market leader in web analytics for granted. With a dedicated Google Analytics Academy that offers how-to guides, training courses, and even certifications to existing Google Analytics users, Google holds its users in an iron grip.

content strategy from Google
Credit: Google.com

The biggest advantage of customer education is retention (which again drives sales at the lowest costs). Another market leader that takes customer education (and retention) seriously is IKEA. From alternate uses for its products to showcasing how customers have creatively used IKEA products to take their lifestyles to the next level, IKEA’s Inspiration section is a design buff’s delight.

content strategy from IKEA
Credit: Ikea.com

Over to You

Drawing and keeping your customers’ attention in this fast-paced marketing age is difficult. Whether it’s your product or marketing that is great, there is someone out there who is doing it better than you and vying for your share of the market. You must constantly attempt to stand out and remain relevant, by relentlessly improving the usability, quality, and effectiveness of your content.

Riding current trends could get your content some short-lived buzz, but it is important to stay focused on pursuing long-term relationships with your customers by creating and publishing content that speaks directly to them.