3 Resource Allocation Questions to Ask for Better Returns

Here are three questions data-driven marketers and those in customer-focused functions need to ask in order to evaluate their resource allocation during uncertain times.

These are obviously times of great uncertainty and change. Smart business people know that with change comes new opportunities. Somewhere, entrepreneurial spirits are already making bets and shifting strategies. There is another powerful axiom, however, which rarely gets enough airtime during times of change: In times of uncertainty, focus on what is certain. One certainty in business is that resources can always be better relocated to achieve better returns.

Unless you are one of the lucky businesses booming in these times, there will be budget cuts. This is the perfect time to reevaluate resource allocations using an agile, data-driven picture of your business. Considering that there are few industries untouched by COVID-19, agile decisions will need to be made based on sparse but recent data.

Here are three questions data-driven marketers and those in customer-focused functions need to ask in order to evaluate their resource allocation.

1. Do I know who my best customers are and are they okay? Your best customers should be based on current sales and lifetime value. Yes, your best customers today are important. However, most businesses survive on the 20% to 30% of customers who are consistently loyal and profitable over many years. Once you have identified the most important customers, you should evaluate if their buying behaviors are changing and why? How can you reallocate resources to better serve this segment?

2. Do I know the channels where most of my business comes from and is it under threat? The first step to answer this question should involve a data-driven accounting of your marketing and sales channels. However, some of your most influential channels may be the most difficult to track. Therefore, it is important that you establish or refresh your multi-touch attribution models so that you can better allocate sales to channels. Right now, it might be very tempting to simply rely on direct attribution or easily measurable channels. After all, this approach feels more certain, but it is rarely the right answer.

3. Do I have the data I need to make quick decisions? If your data was messy and hard to work with before COVID-19, then it will be even less helpful now. This might be the right time to think about the minimal data needed to make agile decisions. The word minimal is critical here as the more data you collect, the more complex the solutions become, and agility diminishes. Do you know what measures are most important? Do you need to spend resources on agile data-driven capabilities?

5 Trends in Customer Experience Software for 2019

I asked people who use customer experience software to share their thoughts on how the software, and its use, will evolve in 2019. Here are five trends to look for this year.

I asked marketers using customer experience (CX) software to share their thoughts on how the technology and its use, will evolve in 2019. Based on this research, I expect CX technologies will evolve in 2019 to support greater system and data connectivity, improve customer insights, and increase message relevance and process automation.

Here are five trends to look for this year.

Integration

M&A activity reflects a trend toward unified customer data platforms and all-in-one solutions for marketing, sales, support, analytics and CX. That’s great for businesses, because soon they won’t need to spend millions on integrations and IT for a single, holistic view of the customer.

We’ll see the introduction of tools and improvement in design to help vertical markets perform integrations more easily, which can find ways to transfer customer information from one application to the other.

Data

Improved integration will help collate disparate customer data to provide a holistic view of customer activity across all departments — sales, marketing, customer support, etc. As CX software improves, organizations will start valuing CX data more than actual goods or services sold, because CX data will have a stronger correlation with long-term revenue generation and profitability.

Customer experience software users say 2018 was the year of data for CX software — from GDPR-mandated data cleanups to a wave of new data from relational and transactional customer interactions, CX software companies focused on data collection. From real-time data collection facilitated by chatbots and AI, 2018 saw a new way for the CX world to gather, store and leverage customer data for more customized engagement. This focus on data will be the foundation for what’s to come in 2019 — a greater focus on data collection, data analysis, and acting on data to increase customer retention and better connect with customers.

CX software will get a chance to show what it can do. We can expect the use of AI to grow and enable companies to sort and evaluate the data collected faster than in previous years. As CX software continues to gather more information, it will also continue to improve the software’s processes and provide better analysis.

Understanding

We see the embedding of more “marketing-like” approaches — more analytics of customer behavior and more automation of responses and customer outreach. CX pros are starting to do this as well, moving away from working only with survey responses from a small number of customers. This is parallel to the development that started some 20 years ago in marketing automation when businesses moved on from small-scale surveys in market research to using all their business data to better understand customers. CX solutions are looking at all data on customers, using it to understand their needs and wants, and building automatic processes to meet those needs.

Businesses are realizing that customers today rate their experience based on the sum of all the interactions with business — not just on call wait time, or Internet ease of use. All of these things come together as customers move seamlessly from one channel to another — they see this as one overall experience. As such, successful CX solutions are embedding tools that can work with the entire customer journey — from its “discovery,” based on journey analytics, to the orchestration of a better overall CX through customer journey management.

Relevance

We’ll see organizations leveraging technology to make customer journeys frictionless, personalized — and ultimately, more profitable. Companies will be able to better target customers with more in-depth information, personalized messaging and tailored recommendations that better align with needs. At the end of the day, it will all come down to how well companies use CX software to learn about their customers and better serve them.

Customers will become more skeptical of companies that fail to personalize emails and content. Consumers respond better when they feel like they’re people, not just another number on a list. The future of successful CX software implementations is those that take the time to focus on personalized, relevant information of value that helps makes customers’ lives simpler and easier.

Artificial Intelligence/Machine Learning

The shiny toys of Augmented Reality (AR), Artificial Intelligence (AI), and data analytics only account for the aesthetic aspects of CX. Many companies are looking at the sexy components of a well-built website while overlooking why customers fell in love with brands like Netflix and Amazon. These top sites and companies gave the people exactly what they wanted from the onset. The next step for companies in 2019 is to find the right balance to effectively blend UX and CX to suit the customers’ needs like never before.

With that being said, the automation side of CX is incredibly powerful. We’ve seen improvements in AI software within the past year and it will be fun to see how much it develops this year. The next couple years will revolutionize CX. Now that companies have built the technology, the only thing left is to fine-tune it. Build on the useful technology put in place.

Machine learning (ML) and AI are already being used to identify data points with the most impact. We will see this translate into providing meaningful action points which leverage the data points.

We will see CX software using AI to predict CX for new products, based on past data with greater accuracy.

Lastly, we will see marketers leveraging AI to learn about their target customers and prompt them to take action to meet their needs.

Laser-Focused Direct Mail With Personas

The best way to increase your chances of great response is to mail to people who are interested in your product or service. There are many ways to do this, but one of the most effective is to create personas.

The best way to increase your chances of great response is to mail to people who are interested in your product or service. There are many ways to do this, but one of the most effective is to create personas.

A buyer persona is a semi-fictional representation of your ideal customer based on market research and real data about your existing customers. Many marketers are familiar with personas in their inbound or digital marketing, but for some reason have not applied them to their direct mail campaigns.

Benefits of Buyer Personas:

  1. Ability to target the right people for each message — send them only offers that they are interested in.
  2. Increase response — better offers equal a better response rate.
  3. Ability to find more prospects like your current customers — when you profile other people you can match them accurately to your current customers.

By creating buyer personas, you can identify who your ideal customers are, where they are and what they want. When you combine this with variable data direct mail you can laser focus your message to each individual based on that person’s persona while getting the benefits of postal discounts for mailing a larger quantity rather than doing a separate mailing for each persona.

We get asked many times, how can we create personas? Here are a few ways you can start researching:

  • Interview or survey current customers — create questions that answer what you need to know in order to build your personas.
  • Review LinkedIn profiles — try to find the common themes between each of your customers.
  • Ask questions on social media — this can give you a larger pool than just your customers, but be careful to fully vet each person responding before you add their input to your research.

After your research there are some best practices for building your personas:

  1. Focus on motives not behavior. Why are they doing what they are doing?
  2. Keep them fictional, but be as realistic as possible. Do not base them off of your most important customer, this can give you a skewed result.
  3. Choose one primary persona, this should be the group of people that will make you the most money.
  4. Create a story for each persona that is explained in five segments:
    • What is their job and demographics?
    • What does a day in their life look like?
    • What are their challenges or pain points?
    • How do they search for information?
    • What are their common objections to your product or service?

There are two big benefits to adding personas to your direct mail. The first is that you can save money on services and postage — and since direct mail’s biggest expense is postage, you can save a lot by not mailing to people who are not interested in what you are offering. The second is by getting more people to respond because they are interested in your offer. So, while you are saving money you are also making more money. It is a win-win situation!

Have you tried using personas in your direct mail? How has it worked for you?

McKinsey Thinks Bland, Generic Loyalty Programs Are Killing Business – And They May Be Right!

A recent Forbes article by McKinsey, “Making Loyalty Pay: Six Lessons From the Innovators,” showed loyalty program participation has steadily increased during the past five years (a 10 percent annual rate of growth), with the average household now having almost 25 memberships. For all of that growing popularity, there are huge questions for marketers: Are the programs contributing to increased sales? And what is the impact of loyalty programs on enterprise profitability?

A recent Forbes article by McKinsey, “Making Loyalty Pay: Six Lessons From the Innovators,” showed loyalty program participation has steadily increased during the past five years (a 10 percent annual rate of growth), with the average household now having almost 25 memberships. For all of that growing popularity, there are huge questions for marketers: Are the programs contributing to increased sales? And what is the impact of loyalty programs on enterprise profitability?

Overall, companies with loyalty programs have grown at about the same rate as companies without them; but there is variance in performance value among industries. These programs produce positive sales increases for hotels, for example, but negative sales impact on car rental, airlines and food retail. And, companies with higher loyalty program spend had lower margins than companies in the same sector which do not spend on high-visibility loyalty programs.

McKinsey has noted that, “Despite relative underperformance in terms of revenue growth and profitability, over the past five years, market capitalization for companies that greatly emphasize loyalty programs has outpaced that of companies that don’t.” This, as they see it, may be indicative of hope among companies with programs that long-term customer value can be generated.

Within the McKinsey report, several strategies are offered for helping businesses overcome the negatives often associated with loyalty programs. Key among these are:

  • Integrate Loyalty Into the Full Experience
    Companies can link the loyalty program into the overall purchase and use experience. An example cited in the article is Starbucks, which has created its program to reflect the uniqueness of its café experience. Loyalty is built into the program by integrating payments and mobile technology, which appeals to its target audience.
  • Use the Data
    This may be the most important opportunity represented by loyalty programs. Data collected from the programs can offer competitive opportunities. Tesco, the largest supermarket chain on the planet, has been doing loyalty program member number-crunching for years through DunnHumby. Similarly, Caesars Entertainment has rich databases on its high-rolling program members. One retailer has combined its loyalty program with a 5 percent point-of-sale discount, building volume from its highest-value customers. In another well-documented example, a retailer has used its loyalty program data to identify future mothers before other chains, thus targeting offers to capture both their regular spend and new category purchases as buying habits evolve.
  • Build Partnerships
    As stated on so many occasions, organizations that build trust generate stronger, more bonded, customer behavior. This applies to loyalty programs as well, where there is ample opportunity to build cross-promotion for customers with non-competing products and services. In the U.K., Sainsbury, the major supermarket competitor of Tesco, has partnered with Nectar, a major loyalty coalition. Nectar has more members than Tesco, and participants can collect rewards across a large number of non-competing retailers. Through partnership, Sainsbury’s offers customers a broader and deeper value proposition; and Nectar also generates data from coalition partners, which it uses to better target promotions to customers.
  • Solve Customer and Industry Pain Points
    Numerous customer behavior studies have shown that people will gravitate to, and pay more for, better service. A perfect example of this is Amazon Prime, where additional payment gets customers faster delivery and digital tracking. This is good for Amazon (estimates are that members spend more than four times more with Amazon than non-members), its customers, and its suppliers, who also get access to Prime customers and the positive rub-off of affiliating with a trusted brand.
  • Maximize Difference Between Perceived Value and Real Cost
    Often, program elements can represent high perceived value without adding much in the way of bottom-line cost to the sponsor. The example cited is Starwood Hotels and Resorts where, through its Starwood Preferred Guest (SPG) program, there is a focus on personal leisure travel rewards for high-spending frequent guests.
  • Allocate Loyalty Reinvestment to the Most Valuable Customers
    Many companies have only recently come to the realization that some customers are more valuable than others; and, to be successful, loyalty programs need to target the higher revenue customers. In 2010, Southwest Airlines revamped its loyalty program to make rewards more proportional to ticket price; and this has better targeted the most profitable customers, as well as enabled the airline to adopt a loyalty behavior metric that is closely tied to actual revenue generation.

Loyalty programs continue to grow, but they are also tending to become more closely integrated with brand-building and multichannel customer experience optimization. But, there is also lots of commoditization and passivity were these programs are concerned—sort of the “If You Build It, They Will Come” syndrome at work. And, of course, there’s a mini contra movement among some retail chains, where they have removed established loyalty programs—or never initiated them in the first place—in favor of everyday low prices and more efficient performance.

What Customer-Centric, Customer-Obsessed Companies Must Do

In building relationships with and value for customers, my longtime observation is most organizations tend to progress through several stages of performance: customer awareness, customer sensitivity, customer focus and customer obsession. Here is the “executive summary” version of some conditions of each stage.

In building relationships with and value for customers, my longtime observation is most organizations tend to progress through several stages of performance: customer awareness, customer sensitivity, customer focus and customer obsession.

Here is the “executive summary” version of some conditions of each stage.

Customer Awareness
Customers are known, but in the aggregate. The organization believes it can select its customers and understand their needs. Measurement of performance is rudimentary, if it exists at all; and customer data are siloed. There’s a traditional, hierarchical, top-down management model, with “chimneyed” or “smokestack” communication (goes up or down, but not horizontal) with little evidence of teaming.

Customer Sensitivity
Customers are known, but still mostly in the aggregate. Customer service is somewhat more evident (though still viewed as a cost center), with a focus on complaint and problem resolution (but not proactive complaint generation; internal groups tend to point fingers and blame each other for negative customer issues). Measurement is mostly around customer attitudes and functional transactions, i.e. satisfaction, with little awareness of emotional relationship drivers. The organization has a principally traditional, hierarchical, top-down management model, with “chimneyed” or “smokestack” communication (goes up or down, but not horizontal), with some evidence of teaming (mostly in areas of complaint resolution).

Customer Focus
Customers are both known and valued, down to the individual level, and they are recognized as having different needs, both functional and emotional. The customer life cycle is front-and-center; and performance measurement is much more about emotion and value drivers than satisfaction. Service and value provision is regarded as an enterprise priority; and customer stabilization and recovery are goals when problems or complaints arise. Communication and collaboration with customers, between employees, and between employees and customers is featured. Management model and style is considerably more horizontal, with greater emphasis on teaming to improve customer value processes.

It’s notable that, at this more evolved and advanced stage of enterprise customer-centricity, complaints are thought of more in terms of a life cycle component, and recovery is more of a strategy than a resolution.

Customer Obsession
Throughout the organization, customer needs and expectations—especially those that are emotional—are well understood, and response is appropriate (and often proactive).

Everyone is involved in providing value to customers—from C-suite to front-line—and everyone understands his/her role. Customer behavior is recognized as essential to enterprise success, and optimal relationships are sought.

Performance measurement is focused, and shared, on what most monetizes customer behavior (loyalty, emotion and communication metrics—such as brand-bonding and advocacy—replace satisfaction and recommendation).

Customer service (along with pipelines and processes) is an enterprise priority, and seen as a vital, and profitable, element of value delivery.

The management model is far more horizontal, replacing traditional hierarchy; and there is an emphasis on teaming and inclusion of customers to create or enhance value.

Companies that are customer-obsessed, and what makes them both unique and successful, have been extensively profiled by consultants and the business press. Often, they go so far as to create emotionally driven, engaged and even branded experiences for their customers, strategically differentiating them from their peers.

In addition, these companies focus on the complete customer life cycle, and much more on retention, loyalty and risk mitigation (and even winback) than acquisition. Support experiences are strategic, nimble and seamless, and often omnichannel. Multiple sources of data are used to develop insights. Recognizing the information needs of their customers, they invest in altruistic content creation (over advertising); and they communicate proactively and in as personalized a manner as possible

Customer obsession, what I refer to as “inside-out” customer-centricity, has been a frequent subject of my blogs and articles: One of Albert Einstein’s iconic quotes reflects the complete dedication of resources and values needed for an organization to optimize its relationships with customers: “Only one who devotes himself to a cause with his whole strength and soul can be a true master.” Mastery requires, as well, a storehouse of experience coming from experimentation; so, just like in the pole vault and high jump, we can expect that the customer-centricity bar will continue to be raised.

Building Customer-Centric, Trust-Based Relationships

More than a buzzword, “being human,” especially in brand-building and leveraging customer relationships, has become a buzz-phrase or buzz-concept. But, there is little that is new or trailblazing in this idea. To understand customers, the enterprise needs to think in human, emotional terms. To make the brand or company more attractive, and have more impact on customer decision-making, there must be an emphasis on creating more perceived value and more personalization. Much of this is, culturally, operationally, and from a communications perspective, what we have been describing as “inside-out advocacy” for years.

More than a buzzword, “being human,” especially in brand-building and leveraging customer relationships, has become a buzz-phrase or buzz-concept. But, there is little that is new or trailblazing in this idea. To understand customers, the enterprise needs to think in human, emotional terms. To make the brand or company more attractive, and have more impact on customer decision-making, there must be an emphasis on creating more perceived value and more personalization. Much of this is, culturally, operationally, and from a communications perspective, what we have been describing as “inside-out advocacy” for years.

Most brands and corporations get by on transactional approaches to customer relationships. These might include customer service speed, occasional price promotions, merchandising gimmicks, new product offerings, and the like. In most instances, the customers see no brand “personality” or brand-to-brand differentiation, and their experience of the brand is one-dimensional, easily capable of replacement. Moreover, the customer has no personal investment in choosing, and staying with, one brand or supplier over another.

A key opportunity for companies to become stronger and more viable to customers is creation of branded experiences. Beyond simply selling a product or service, these “experiential brands” connect with their customers. They understand that delivering on the tangible and functional elements of value are just tablestakes, and that connecting and having an emotionally based relationship with customers is the key to leveraging loyalty and advocacy behavior.

These companies are also invariably quite disciplined. Every aspect of a company’s offering—customer service, advertising, packaging, billing, products, etc.—are all thought out for consistency. They market, and create experiences, within the branded vision. IKEA might get away with selling super-expensive furniture, but it doesn’t. Starbucks might make more money selling Pepsi, but it doesn’t. Every function that delivers experience is “closed-loop,” carefully maintaining balance between customer expectations and what is actually executed.

In his 2010 book, “Marketing 3.0: From Products to Customers to the Human Spirit,” noted marketing scholar Philip Kotler recognized that the new model for organizations was to treat customers not as mere consumers, but as the complex, multi-dimensional human beings they are. Customers, in turn, have been choosing companies and products that satisfy deeper needs for participation, creativity, community and idealism.

This sea change is why, according to Kotler, the future of marketing lies in creating products, services and company cultures that inspire, include and reflect the values of target customers. It also meant that every transaction and touchpoint interaction, and the long-term relationship, needed to carry the organization’s unique stamp, a reflection of the perceived value represented to the customer.

Kotler picked up a theme that was articulated in the 2007 book, “Firms of Endearment.” Authors Jagdish N. Sheth, Rajendra S. Sisodia and David B. Wolfe called such organizations “humanistic” companies, i.e. those which seek to maximize their value to each group of stakeholders, not just to shareholders. As they state, right up front (Chapter 1, Page 4):

“What we call a humanistic company is run in such a way that its stakeholders—customers, employees, suppliers, business partners, society, and many investors—develop an emotional connection with it, an affectionate regard not unlike the way many people feel about their favorite sports teams. Humanistic companies—or firms of endearment (FoEs)—seek to maximize their value to society as a whole, not just to their shareholders. They are the ultimate value creators: They create emotional value, experiential value, social value, and, of course, financial value. People who interact with such companies feel safe, secure, and pleased in their dealings. They enjoy working with or for the company, buying from it, investing in it, and having it as a neighbor.”

For these authors, a truly great company is one that makes the world a better place because it exists. It’s as simple as that. In the book, they have identified about 30 companies, from multiple industries, that met their criteria. They included CarMax, BMW, Costco, Harley-Davidson, IKEA, JetBlue, Johnson & Johnson, New Balance, Patagonia, Timberland, Trader Joe’s, UPS, Wegmans and Southwest Airlines. Had the book been written a bit later, it’s likely that Zappos would have made their list, as well.

The authors compared financial performance of their selections with the 11 public companies identified by Jim Collins in “Good to Great” as superior in terms of investor return over an extended period of time. Here’s what they learned:

  • Over a 10-year horizon, their selected companies outperformed the “Good to Greatcompanies by 1,028 percent to 331 percent (a 3.1 to 1 ratio)
  • Over five years, their selected companies outperformed the “Good to Great companies by 128 percent to 77 percent (a 1.7 to 1 ratio)

Just on the basis of comparison to the Standard & Poor’s 500 index, the public companies singled out by “Firms of Endearment” returned 1,026 percent for investors during the 10 years ending June 30, 2006, compared to 122 percent for the S&P 500—more than an 8 to 1 ratio. Over 5 years, it was even higher—128 percent compared to 13 percent, about a 10 to 1 ratio. Bottom line: Being human is good for the balance sheet, as well as the stakeholders.

Exemplars of branded customer experience also understand that there is a “journey” for customers in relationships with preferred companies. It begins with awareness, how the brand is introduced, i.e. the promise. Then, promise and created expectations must at least equal—and, ideally, exceed—real-world touchpoint results (such as through service), initially and sustained over time, with a minimum of disappointment.

As noted, there is a strong recognition that customer service is especially important in the branded experience. Service is one of the few times that companies will directly interact with their customers. This interaction helps the company understand customers’ needs while, at the same time, shaping customers’ overall perception of the company and influencing both downstream communication and future purchase.

And, branding the customer experience requires that the brand’s image, its personality if you will, is sustained and reinforced in communications and in every point of contact. Advanced companies map and plan this out, recognizing that experiences are actually a form of branding architecture, brought to life through excellent engineering. Companies need to focus on the touchpoints which are most influential.

Also, how much influence do your employees have on customer value perceptions and loyalty behavior through their day-to-day interactions? All employees, whether they are customer-facing or not, are the key common denominator in delivering optimized branded customer experiences. Making the experience for customers positive and attractive at each point where the company interacts with them requires an in-depth understanding of both customer needs and what the company currently does to achieve that goal, particularly through the employees. That means companies must fully comprehend, and leverage, the impact employees have on customer behavior.

So, is your company “human”? Does it understand customers and their individual journeys? Are customer experiences “human” and branded? Is communication, and are marketing efforts, micro-segmented and even personalized? Does the company create emotional, trust-based connections and relationships with customers? If the answer to these questions is “YES,” then “being human” becomes a reality, the value of which has been recognized for some time, and not merely as a buzz-concept.

Emails That Target Customer Behavior Without Using Big Data

The ever increasing volumes of data used by companies like Target, Walmart and Amazon to carefully target their customers is cumbersome and difficult to manage. Analyzing patterns to find the right trigger that will motivate an individual to buy requires gifted statisticians that combine art and science into marketing magic. But what if you are not quite ready to use big data in your business? Can you still reap some of the benefits?

The ever increasing volumes of data used by companies like Target, Walmart and Amazon to carefully target their customers is cumbersome and difficult to manage. Analyzing patterns to find the right trigger that will motivate an individual to buy requires gifted statisticians that combine art and science into marketing magic. But what if you are not quite ready to use big data in your business? Can you still reap some of the benefits?

Fortunately for companies that don’t have a team of statisticians standing by, customer behavior and activity can be used to increase sales without the challenges that come with big data. It’s as simple as watching for specific activity or changes in customer behavior and being prepared with a customized response to encourage people to buy.

If this is your first venture into customer behavior marketing, start with the people who are the easiest to identify. Seasonal and discount shoppers are relatively easy to recognize because they have very specific buying patterns. Creating customized marketing for them increases their response and reduces costs. The dual benefits make this a logical place to begin.

Seasonal shoppers are the people who purchase items at specific times of the year. Traditional RFM (recency, frequency, monetary value) analytics flag them as top buyers shortly after a purchase and then systematically move them down the value chain. When they place the next order, they move back to the top and flow down again. Creating a marketing plan that sends materials when they are most likely to buy reduces marketing costs without affecting sales.

Discount shoppers only buy when there is a sale. This segment can be further divided into subsets based on how much discount is required to get the sale. If the marketing is properly tailored, this group of people serves as inventory liquidators. Minimizing the non-sale direct mail pieces they receive and heavily promoting sales increases revenue while reducing costs.

Both groups respond well to promotional emails. Capturing email addresses should be standard operating procedure. It is especially critical for seasonal and discount shoppers because they tend to be more impulsive than other segments. The emails that remind seasonal shoppers that it is that time again and tell discount buyers about the current sales are economical and effective.

The next step after targeting shopper segments is adding specific product category information based on the individual’s shopping history. When my daughter was younger, my shopping behavior with American Girl included two orders per year for regular priced items and sale purchases in between. The two full price orders were placed just before Christmas and her birthday. Sale purchases were impulse driven and triggered by emails announcing clearance items.

Bitty Baby was the category of choice in the early years of buying from American Girl. The shift to the character dolls didn’t happen until my daughter was nine. She received her first Bitty Baby at two. During nine years of systematic purchases, no one recognized that I only ordered certain things at specific times. How much would your company save if your marketing was tailored to customer purchasing patterns?

What about targeting people who haven’t purchased from a specific category?

The ability to predict what people want before they know it is one of the advantages of analyzing trends and activity in big data. Before moving to that level, start with the information that shoppers are providing. This trigger email from Amazon was sent two weeks after I searched for soda can tops on their site without purchasing.

The email avoids the creepy factor by saying, “are you looking for something in our Kitchen Utensils & Gadgets department? If so, you might be interested in these items.” Instead of, “because we noticed that you spent 14.34 minutes searching for soda can tops you may be interested in the ones below.”

The best practices included in this email are:

  • It doesn’t share how they know that the shopper is interested in a specific category or item.
  • The timing from the original search to email generation is long enough to allow time to purchase, but not so long the search is forgotten.
  • It makes accessing the items easy by providing multiple links.
  • The branding is obvious with links to my account, deals and departments.

Targeting customer behavior can become very complicated very quickly. Starting simple with specific segments and activity allows you to test and build on the lessons learned. The return on investment is quick and may surprise you.

Branding Is Not Enough to Make Social Sell

If you want to make social media sell for you take action on the mercenary truth: Branding is rarely executed as a consistent, reliable process. Branding (the meaning of which is still not universally agreed upon) is not enough to create sales. Nor is B-to-B branding—or its “social cousin” engagement—consistently able to produce customer behavior (e.g., leads). Direct response must be built in to the campaign for leads and sales to manifest. It doesn’t “just happen” thanks to our friends branding and engagement.

If you want to make social media sell for you, take action on the mercenary truth: Branding is rarely executed as a consistent, reliable process. Branding (the meaning of which is still not universally agreed upon) is not enough to create sales. Nor is B-to-B branding—or its “social cousin,” engagement—consistently able to produce customer behavior (e.g., leads). Direct response must be built in to the campaign for leads and sales to manifest. It doesn’t “just happen” thanks to our friends branding and engagement.

Customers Expect Proof, Upfront
People are buying as a result of content marketing efforts. True. But they’re buying when the business behind the content is willing to prove effectiveness of the product or service (in some small but meaningful way) prior to purchase. This is so important you might want to read it again.

Here’s the rub. In my experience, branding and engagement prove little (if anything) to me, the customer. Branding and engagement usually fail to solve a problem that brings me closer to the purchase as part of a clearly defined process.

Think about how you use Facebook, LinkedIn, YouTube, etc. in your life. Do you buy based on what you see on social media? You’re probably not buying based on sentiment (how you feel about a brand) very much any more. In fact, you’re likely buying less based on how engaged marketers think your are, more based on what they’ll prove to you up front!

Prove It or Lose It!
Today, people are buying purely based on a brand’s ability to deliver some results before the purchase. Software? Give me a free trial—and don’t give me any talk about limiting functionality of the trial version. Financial services? Solve a problem for me relating to my ultimate need—to get my act together with college savings or retirement. Consulting? Show me, materially, that you’re worth your salt. You get the idea. And, no, this isn’t about “free” as a new business model.

Delivering results before the purchase demands a systematic, yet practical, way to court your customer—to prove to them that actually buying your product or service will certainly give them full results. They’ve got to be sure and nothing creates certainty like actual proof! So, how can you begin to take next steps?

“In most companies, at least historically, marketing and sales have been measured by, and hence driven by, different success metrics,” says Dan McDade of Pointclear, a B-to-B lead generation firm who points at the classic misalignment of sales and marketing as problematic.

“This condition has been simply accepted by or ignored by most senior managers. I know this seems harsh, but unfortunately it is still true today in many, if not most, organizations,” says McDade.

Reach Past Listening, Toward Useful Insights
Recognition of the misalignment is step one, and I’ll ask you to pair this recognition with a new perspective on social media. Start applying social media to uncover insights on customers’ micro-problems, goals or burning desires, then putting those discoveries to work through traditional lead nurturing.

Some argue the big opportunity social gives us is to create more engagement in hopes of creating preference. But successful social sellers use social media to create demand. In parting, which of the below seems more powerful to you?

  1. Listening for customers’ brand perceptions, sentiment, etc. and creating better ad messaging that creates more engagement (awareness leading to preference).
  2. Understanding customers’ problems or goals and finding creative ways to create organized, measurable response that helps customers “guide themselves” toward a purchase.

Thanks for considering.

The Database Marketer Superhero: Expanded Role, Big Impact

Riddle me this, Batman: What sort of marketing strategies today require deeper, strategic database insight? Not so puzzling, is it? Pretty much everything a marketing team does today is driven by data — e.g., digital outreach, content, media, attribution, return on investment analysis, lead nurturing, PR and social community participation. In fact, the list would be shorter if we tallied up those marketing functions that don’t benefit from data-driven decisions.

Riddle me this, Batman: What sort of marketing strategies today require deeper, strategic database insight?

Not so puzzling, is it? Pretty much everything a marketing team does today is driven by data — e.g., digital outreach, content, media, attribution, return on investment analysis, lead nurturing, PR and social community participation. In fact, the list would be shorter if we tallied up those marketing functions that don’t benefit from data-driven decisions.

Database marketers were traditionally the geeks of the marketing department. They kept to themselves, ran queries to answer questions posed by other strategists, and worked hard to keep data clean and updated. Today’s database marketers are part of an emerging and essential marketing operations team that’s driving a lot of brands’ strategies. One marketer said to me recently, “Whomever knows the customers best gets to make the call.” Who knows your customers better than the people working with the data every day? All of a sudden, database marketers are superheroes — or at least have the opportunity to wear capes if they choose to accept the challenge.

There are two factors driving this trend, one being consumer habit. Given the ability and choice to interact with brands in many ways and across many channels, consumers are taking full advantage. It’s a me-centered consumption world where customer preference and whim create habits. At the same time, marketing automation technology is advancing and data integration is possible. Marketers can track and, more importantly, react to customer behavior in order to meet needs across channels.

Consider these five initiatives that have become imperatives for many chief marketing officers today:

1. Obtain a 360-degree view of the customer. One B-to-C marketer told me that there are more than 25 ways customers can interact with her brand, from a kiosk to a store counter to email to mobile commerce to branded website to call center to social communities. Most consumers participate in three or more of those channels. Communications can only be optimized if those habits and experiences are captured — and actionable — in your database.

2. Respond to customer behavior in the channel where the interaction occurred. This also has to be aligned with self-selected preferences.

3. Select the optimal channel for your next offer. A hotel owner uses past booking behavior to send last-minute alerts via SMS to those who have opted in and accessed the brand’s mobile commerce site. All others get the information via email. Response has boosted overall 8 percent.

4. Outline personas representing key customer segments. Do this in order to profile audience types and improve communication messaging and cadence.

5. Test and optimize your mix of channels for lead nurturing campaigns. For a live seminar event, one B-to-B marketer emailed reminders and offers based on interaction with previous email campaigns. Those who didn’t respond got simple reminders on date, location and keynote speakers. Those who did respond got more robust offers. Revenue from the offers increased 50 percent over the previous year and spam complaints dropped 25 percent. This is surely because those who demonstrated a willingness to engage prior to the event were nurtured with offers that made sense to their actions, and the others were left alone.

I’m sure there are infinite variations of these opportunities. Perhaps you’re testing some of them now. It will also be great to see how database marketers react to this new level of attention and interest from the C-suite. Will you embrace it and join the strategists, or will you run back to the corner and take orders?

How are you and your team embracing the need for a data-driven marketing approach? Please tell us by posting a comment below.