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.

multichannel graphic
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.

multichannel chatbot
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.

multichannel chart
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!

Why Marketers Should Tap Into the Potential of Bing Ads, the Dark Horse of the Search World

With the introduction of the Microsoft Audience Network (MSAN), enhanced AI capabilities and increased partnerships within the last 12 months, Bing Ads is becoming an even more advanced channel that should be tapped to effectively reach the right audience at key moments.

Bing has often been an overlooked publisher in the search world, left in the shadows of its older rival, Google Ads, and simply not given the credit it’s due. However, marketers shouldn’t overlook the dark horse that is Bing Ads. With the introduction of the Microsoft Audience Network (MSAN), enhanced AI capabilities and increased partnerships within the last 12 months, Bing is becoming an even more advanced channel that should be tapped to effectively reach the right audience at key moments.

Partnerships and AI

The long-standing partnership between Microsoft, AOL and Yahoo continues to evolve; starting in March 2019, Bing began exclusively servicing Yahoo Search traffic, which included traffic currently acquired from Oath Ad Platforms (previously known as Yahoo Gemini) and other search platforms. With Microsoft’s acquisition of LinkedIn came the ability to target LinkedIn users based on job function and title, an exceptionally important development for those in the B2B sector, and a feature that Google simply cannot match.

A few key placements and sites unique to Bing that marketers should consider adding to their advertising efforts include the trifecta of MSN, Microsoft Outlook and Microsoft Edge. This trifecta enables marketers to deliver high-quality native ad placements across devices regardless of audience, while benefiting from Bing’s promise never to show ads next to sensitive categories such as tragic current events to help protect brands. Bing offers two layouts for native ad formats: image-based ads and feed-based ads. Imaged-based ads are highly visual and appear across multiple types of platforms. Plus, a big bonus to marketers is the ability to import their current assets from what they’re already running on the Google Display Network (GDN) or Facebook. Feed-based ads are product-based and require the use of product audiences which retarget customers on products they’ve already viewed or even added to cart but didn’t finish the check-out process.

Chatbots offer another great way to provide on-demand answers to customers, and Microsoft and Bing stand are at the forefront. This real-time ad extension format can inspire users to purchase an item or answer specific questions to help better service their needs. In fact, Bing projects that 95 percent of customer interactions will be powered by AI bots by 2025. This is something that Bing has been testing for some time now, but Google has barely set in motion.

The MSAN Factor for Bing Ads

There’s been a lot of talk about keywords becoming a thing of the past and looking toward audiences as the means to effectively reach consumers in the future, causing a ripple effect across the industry. In fact, Google AdWords dropped ‘Words’ from its name last June (announced at Google Marketing Live 2018), as the company transitions its focus to the ads themselves. But what does Bing have going for it in this aspect that Google doesn’t? The MSAN component. MSAN is powered by AI and machine learning known as the Microsoft Graph. This intelligent tool contains search and web activity and helps isolate trends to help reach a marketer’s target audience. Bing does not allow for commercial data contained in the Graph to be used for targeting ads; any data is privately stored, owned and anonymized by Bing — a critical factor in a world where privacy is at the forefront of both consumers’ and marketers’ minds.

MSAN and Google Ads’ audience network have similarities like remarketing, in-market, custom audiences and product audiences. Additionally, advertisers can target by age, gender location and device. But the real shining star of MSAN and Bing Ads is LinkedIn profile targeting. This unique feature allows advertisers to apply LinkedIn targeting to campaign and ad group levels and target by industry (with up to 145 unique industries), by company name (over 80,000) and by job function (26). Marketers can apply these targeting settings for text ads, shopping and dynamic search ads.

Artificial Intelligence Ethics

Marketers are not the only ones watching Microsoft’s next move. In a surprising revelation, the Vatican is teaming-up with Microsoft for a prize to “promote ethics in artificial intelligence.” Pope Francis even met with Microsoft’s President Brad Smith on Feb. 13 to discuss the Catholic church’s position on AI. The person who best defends their dissertation on ethical concerns involving AI will win a trip to the Microsoft headquarters and a prize of 6,000 Euros.

With all the recent talk around privacy concerns and the role tech giants play, it’s a smart move for Microsoft to approach the apprehensions head-on. It’s particularly timely since President Trump announced an executive order earlier this month outlining a plan on how the country will get ahead of AI and how the government can work directly with AI companies. However, with the public scrutiny of Facebook’s Cambridge Analytica data leak scandal and Google’s share of privacy concerns, Microsoft is proving its reputation with no major incidents top-of-mind. The Microsoft Graph provides   another layer to help reassure their commitment to protecting consumer data.

If marketers have been on the fence about tapping into Bing Ads’ potential, there is no greater time to start acting on it than now. Bing’s increased partnerships, addition of MSAN and intelligent solutions, and commitment to ethical responsibilities shouldn’t be underestimated. The odds may not have favored Microsoft products like Bing in the past, but these innovations mean marketers’ investments now will pay high dividends in the future.

7 B2B Marketing Predictions for 2019

From chatbots to data-driven marketing, from the inevitable backlash against martech to the broadened use of social media, Ruth Stevens presents her seven predictions for what’s to come in 2019 for B2B marketers.

Crystal BallI am adding my voice to the chorus of observers who predict various developments in 2019 for B2B marketing. My policy is to avoid reflecting on my past predictions, which are likely unrealized and full of errors. Instead I shall boldly go forth, with my sense of what we are likely to see this year, and damn the torpedoes.  My B2B marketing predictions — seven in all — range from marcom to data. Your comments are welcome!

  1. B2B marketing communications become more human. Our field has long focused on selling to entities — accounts, buying groups, with rational, specific needs — and so we tend to stick to the facts. But it’s time to be more human. To talk to the buyers as individuals, in a language that moves them. So Forrester predicts, and I agree. I applaud Gyro for taking the initiative on some very interesting research around this topic. The study reveals the feelings business buyers seek in response to our offerings, feelings like confidence, optimism and accomplishment. Let’s give it to them!
  2. An inevitable backlash against martech. The backlash is already starting, but look for it to pick up. I wrote about this in 2014, saying we must not confuse marketing automation for marketing strategy. As martech grows, inevitably B2B marketers are realizing that it’s not the silver bullet they had hoped for. Justin Gray, founder of LeadMD, points out that only about 1% of deals can be tied to MA. We’ve got some ‘splainin’ to do.
  3. Marketers will finally supply sales with the help they really need. My fervent wish, anyway. Tip of the hat to Gavin Finn, who eloquently explains this need in a recent Entrepreneur article. If we marketers are not helping sales communicate a differentiated value, producing truly effective content, and developing insight into the detailed needs of the buying group, we should all fire ourselves.
  4. Broaden the use of social media. Social is no longer a nice-to-have in B2B. It requires thoughtful strategy, real budget, and a keen integration with the rest of the marketing mix. Plus continued experimentation with new opportunities. Video will continue to grow. And B2B marketers will try new channels, like Quora, a place where people pose questions and get answers from other individuals. It’s ripe for business problems to be solved.
  5. Chatbots go mainstream. Perfect for B2B, chatbots serve global customers, around the clock, with fast, accurate and cheap service. This is all good.  But my favorite benefit for B2B marketers? Chatbots give you a third method for turning your website into a lead generator (after web form-fill and IP address identification). And the AI continues to improve, daily.
  6. Will CX be the B2B buzzword of 2019? Like ABM in 2017, and intent data in 2018. I’m predicting a surge of interest in the power of providing superior customer experiences — not limited to digital, but across all customer touchpoints in B2B. Think about it. We operate with a limited universe of customers and prospects. We are burdened with long sales cycles, but the payoff is high-ticket sales. We can’t afford to lose an account.  CX is the next competitive frontier.
  7. As ever, B2B success is undergirded by data. Marketers will continue to understand, and act upon the need for clean, complete and accurate data coverage of their market opportunity.  This is why Theresa Kushner and I published B2B Data-Driven Marketing, soon to be available via Kindle.  A new study from MX Group confirms: The Number 1 characteristic of top performing B2B firms is “Have good data.”  What’s Number 2?  “Have effective lead follow-up,” of course!

Happy 2019 to us all.

A version of this article appeared in Biznology, the digital marketing blog. 

Financial Institutions Can Put Artificial Intelligence to Much Better Use

I’ll start with a potentially controversial statement. Banks are misallocating their investment in artificial intelligence and predictive analytics by putting it into consumer-facing chatbots, rather than using it internally to empower their staff to understand and better serve the customer.

I’ll start with a potentially controversial statement. Banks are misallocating their investment in artificial intelligence and predictive analytics by putting it into consumer-facing chatbots, rather than using it internally to empower their staff to understand and better serve the customer.

Most customers don’t like speaking with bots and usually call their bank when they have an issue that requires processing that’s beyond what artificial intelligence can currently offer. In fact, AI’s reputation has been damaged virtually beyond recovery by the endless loop most customers encounter when they call the bank, not able to get to where they want to go.

Moreover, you don’t see pictures of chatbots pinned up in banks with “Employee of the Month” emblazoned across the bottom. Nor was any new business won on the strength of a chatbot’s performance. Finally, customers don’t stay with banks because they developed a great working relationship with a chatbot. Truth of the matter, chat hasn’t reached the level where it’s consistently reliable for addressing the customer concerns that rise to the level of making a call to a financial institution.

All that said, artificial intelligence is a highly powerful tool. How it’s being used is simply being misallocated. So the question becomes, is there a way banks can use it to enhance human engagement with clients? The answer is, “Yes.” Although banks and other financial institutions are in a completely different line of business than, say, a luxury retailer or car dealership, what they have in common is that critical need to engage customers at various points in a given transaction. This applies to banks and other financial institutions at least as much as it applies to other businesses. Reaching out to, connecting with and maintaining relationships with customers, and doing it well, is a key consideration. Done well, banks have a better chance of securing a higher lifetime value from their clients when they get it right. And it’s much harder for bankers or advisers to know about the hundreds of products that are available to them; far more so than, say, a car salesman at a dealership, or an associate in the dress department at Saks. AI’s best use is providing them — the customer-facing bank advisers — with the tools to have the right information for the right client, so they can spend more time on the customer relationship.

There are ways in which the power of predictive analytics can be brought to bear immediately, creating a more substantial and recognizable benefit for both financial services providers and their customers. A knowledge-driven approach to cross-selling and upselling is one such strategy.

There’s a vast range of training, tools and processes that can positively influence engagement efforts. But predictive analytics can push these initiatives into a much higher gear, providing a uniquely powerful impact when it comes to solidifying those all-important bonds with customers. Through better analysis and use of data that’s already available to most financial institutions in petabytes, it’s possible to learn more about customers, and consequently offer them more relevant service, support and product options. The right, internal approach to applying predictive analytics, therefore, results in benefits for both customers and the financial services providers they work with — a true win-win situation.

Historically, banks — especially large ones — tend to lean more toward conservative, careful approaches to new strategies and technology than quick movement and adoption. Given the mound of compliance mandates that govern their every engagement, this is understandable. But it but can be a significant drawback. This is where predictive analytics can sharpen their game. Many institutions have demonstrated a resistance to adopting this specific tool, or have used it in a very limited way. But they’re missing out on the benefits. And understanding the inherent pitfalls in predictive analytics is key to achieving success in deploying it.

How Financial Institutions Can Effectively Deploy Predictive Analytics

It’s a given that cross-selling and upselling help create more lifetime value from customers. But finding strong connections between products and clients is still a complicated process; particularly when you have to juggle moving parts, such as customer credit scores, income, credit utilization, and the like. Figuring out what products you can sell to whom, and predicting what those outcomes will be, constitutes a successful cross-sell. When done correctly and ethically, cross-selling can ultimately strengthen the customer relationship into a lifetime value — read, profitability — for the bank. This is because they’re able to match a product that was needed with a demand that they’ve identified.

It’s 20/20 hindsight, but we all know about the debacle of Wells Fargo’s unethical cross-selling and upselling, and how much trouble it got into as a result. With upselling, predictive analytics can really make a difference in the campaign to upsell. And unlike the Wells Fargo situation, this approach is sustainable. Looking through vast amounts of consumer data can help banks to understand how relationships have historically evolved between the bank and its consumer over time. On the consumer side, the spotlight is on how their data is being used. Only by robust analysis of customer behavior — ideally where multiple products are being offered — can banks regain their customers’ trust that their data is being used to benefit them.

Predictive analytics platforms can conduct this type of analysis, leaning on demographic information, as well as purchasing and financial data that institutions already have from past customer activity. All in real-time. Such an analysis would be prohibitive in terms of time, were trained experts to do the crunching. The predictive analytics tool can then offer sharply defined, personalized, relevant recommendations for staff members to share, while they continue to provide the critical human element in the cross-selling and upselling processes.

Where does this data come from? The sheer volume of payments data that banks gather, whether credit card, utilities, rent or many more — can inform what financial product the customer might be looking for and can afford, creating a sharper, more relevant offering. And that’s where artificial intelligence and predictive analytics can play a role that helps bankers sharpen their game and engage more successfully with their customers, without throwing them on the mercy of the bots. Incidentally, it also proves the notion that artificial intelligence is less about displacing humans and more about helping them perform higher-value work.

Securing profitable customers — back to the lifetime value concept — is job No. 1 for banks, whether small or large. Successfully cross-selling — truly matching a product with an identified need — goes a long way to strengthen that customer relationship. The current financial services landscape is ripe for improvement through the use of predictive analytics. Many institutions are already using advanced analytics, tied to marketing and basic interactions — but few have developed strong processes that focus on understanding customer habits and preferences. From there, they can use predictive tools to become more relevant, valuable — and humanly available — to their clients. The institutions that manage to do so will have an advantage in building stronger, longer-lasting relationships and will enjoy the increased value that comes from them.

With thanks to Carol Sabransky, SVP of Business Development, AArete, who made substantial and insightful contributions to this article.

The Omnichannel Customer Service Gap

As part of our analysis of the omnichannel experience today in the report “Omnichannel Marketing: The Key to Unlocking a Powerful Customer Experience,” we asked marketers how they provide customer service in each channel, and whether or not they are getting AI involved.

As part of our analysis of the omnichannel experience today in the report “Omnichannel Marketing: The Key to Unlocking a Powerful Customer Experience,” we asked marketers how they provide customer service in each channel, and whether or not they are getting AI involved.

The Extent of Omnichannel Customer Service

Here’s what the marketers had to say:

Omnichannel Customer Service chart from the Omnichannel Marketing Report, 2018.

Perhaps not surprisingly, 82 percent of marketers offer live customer service over the phone, 73 percent through email and 52 percent through social media. But only 28 percent offer live service through website chat, and almost none do via virtual assistants (which is an emerging field).

Very few respondents are dabbling in AI or AI-assisted customer service. However, 14 percent do so through web chat — which means half of all web chat is being handled by AI. That’s followed by social media and email.

Outside of website chat bots, AI customer service is still a rare experience. Also, marketers do not yet seem to consider virtual assistants and smart speakers to be important service channels.

Is That Futuristic Enough?

I was a bit surprised that service was not offered more frequently in more channels. Only half of respondents said they offer customer service reps via social media. Tiny numbers offered it through website chat or virtual assistants.

Is that a wide enough spread of service options to satisfy today’s omnichannel customer? Is it enough to be considered “Omnichannel Customer Service”? On the flip side, does limiting those options make for a better service experience?

Beyond the number of channels service was offered in, it seems that very few marketers are leveraging AI for customer service in any channels. Helping customers still means connecting them with live CSRs. Is that really the most efficient way to do things?

The slower customer service is, the higher the chance you’ll lose that customer to a competitor. Offering service on more channels should help you ensure a great experience. Using good AI to assist your CSR’s should reduce friction and make the process more efficient.

What’s holding marketers back here? Is it the fear that an already damaged experience is going to be made worse? Well, I certainly don’t think the robots are going to do a worse job than crowdsourcing that service.

If you’re nervous about creating a chat bot, we’ve got a great session coming up at the All About Marketing Tech virtual conference that will help you learn the basics and build a chatbot that doesn’t suck. Check i out.

And for more about how marketers are building their omnichannel customer experiences, click here to download the complete report for free.