Category: customer intelligence
Shamir Duverseau

How Mature is Your Digital Experience?

According to MIT Sloan Management Review, “digital maturity goes beyond technology … it’s about how businesses are adapting in a digital environment.” Organizations must strive to make digital core to their business—in all areas of their business—in order to succeed. As a marketing leader you have a key question to answer: Are you fundamentally adapting your customer experience to compete effectively in the digital era?

Answering this charge requires an understanding of what digital maturity looks like vis a vis the experience you are providing to customers—from awareness to conversion and beyond—as well as the ability to measure where your organization falls on the spectrum of digital development. The closer you can get to a real-time, 1:1 experience with each person, the more mature your digital experience. Why? Because the more personal the experience, the more likely someone is to take action in the short term and build lifetime value for your organization in the long term. 

To illustrate the importance of the 1:1 experience, consider this example. Smart Panda Labs worked with a real estate development company offering luxury apartment rentals in metropolitan areas including New York, Chicago, and Los Angeles. As with many organizations, the homepage was one of most frequented pages on their website and featured general messages about the company and their newest properties. As we helped this brand mature their digital experiences, homepage content became more personalized. Direct visits to the site prompted location-specific content. Visitors coming to the site by way of a paid search campaign would see content related to their search query. Their behavior on the site further informed home page content, as they searched specific neighborhoods or property types. As this personalization increased, so did engagement and conversions.

Just as no child grows up overnight, no organization can become digitally mature overnight, either. The arc of digital experience growth can be summarized in four stages: Early, Developing, Maturing, and Leading.

The Early Stage

If your organization is in the early stage of digital maturation, the digital experience you are providing to consumers is not fully formed. Maybe you are still just talking about how to personalize the journey, but you have yet to put those wheels in motion. 

To progress to the next stage, you’ll need to focus on clarifying your vision, goals, and strategy and communicating that vision across the organization. What are the fundamental ways you will build awareness for your brand in the digital space? How will you get prospects to consider your products or services? What can help them make a decision and choose your brand over the competition? How can you keep them as customers? And finally, how can you transform them from loyal customers into adoring fans?

As you answer these questions, focus on how you’re building your foundation—the elements necessary to execute, measure, and learn from basic tactics. The emphasis here should be on learning, which is a critical thread that must be pulled through each stage of your organization’s growth and maturity.

The Developing Stage

In the developing stage, your organization is focused on framework—the parameters and processes that must be in place to engage in slightly more advanced digital tactics. Not only will these more robust tactics begin to drive better results, they will also begin to provide more meaningful data, and data is the gas that will fuel the personalization to which every brand aspires.

While the basics afford you the ability to gather data, a framework enables you to  gather meaningful customer data on which you can act.  

It is this kind of data that positions you to explore personalizing the experiences you are creating, if not to individuals at least to groups (audience segments).  

The Maturing Stage    

Jeff Bezos once said of Amazon: “Our success is a function of how many experiments we do per year, per month, per week, per day.” In today’s digital world, more and more companies are turning to experiments to discover how best to create or improve online experiences. A maturing stage organization is concerned about having an organizational culture that promotes experimentation, and one where learning is part of every digital tactic. 

Personalized experiences are driven by the needs and desires of your  prospects and customers. Experimentation is essential to uncovering what those needs and wants are. 

The mindset that fosters experimentation is one of trusting the process. It’s about the journey, not the destination. People’s circumstances and, therefore, preferences change constantly. Add to that the effects of the marketplace, and you quickly come to recognize that personalization is never fixed. Knowing an individual’s (or a segment’s) needs and desires requires constant testing, which can only be supported by a thriving organizational culture of experimentation. (Learn more about the importance of such a culture and how to achieve it in the Harvard Business Review article “Building a Culture of Experimentation”.)

 The Leading Stage

When you have arrived at the leading stage, you’re focused on your team. You have invested in your organization, and your team has used that investment to build you a strong foundation, a solid framework, and a pervasive culture. Now it’s time to make sure you are investing in their learning and growth.  

Remember, while data may fuel the digital experience, it is people who fuel your organization. The right team will not only enable your strategy to thrive, they will have the mindset and the skills to evolve and iterate that strategy in an ever changing world. Those iterations will necessitate changes to your foundation and framework to provide the proper support. It is your team that will lead and manage those changes. Furthermore, it is people who bring life to and maintain culture, so it will take the right people to live the culture you have built as a maturing organization.

Ultimately, the right people will bring you the greatest return on your investment.

What’s Next?

Every organization is different, varying by size, industry, and market. However, the tactics that lead to a mature digital experience are fundamentally the same. How well you execute on these tactics, across all digital experiences, is what will win you loyal customers and increase their lifetime value.

Knowing where you are in this trajectory requires asking yourself some direct questions about the digital experiences you are (and aren’t) currently providing. Understanding your baseline is essential to your growth. Ready to find out? Take this quiz.

Once you decide you’re ready to evolve your digital experiences to the next stage, you’ll need a roadmap to get there. Understanding these next steps will be the subject of a future article. 

Category: customer intelligence
Shamir Duverseau

Humanize Data with Creative Intelligence

We hear a lot about data science these days, and well we should. It’s clear data is the new oil and the ability to gather accurate data can yield brands a great deal of power. That power can be used to fuel the Customer journey from awareness to purchase to loyalty and evangelism.

But something else has also become clear, or at least it should be. It’s not all science. It’s also an art. Science, in this context, can be defined as the systematic study of behavior through observation and experimentation. Then there’s art. Art is the expression and application of human creative skill.  And in that definition lies the key. Art is human.

Science, in a sense, removes the human part of the equation as it to move one closer to objectivity, and there’s no doubt that’s important. But it’s critical not to forget that no matter how much data we have, it’s data about people. People who are, more often than not,  subjective creatures with feelings and inclinations and needs that are hard, if not impossible, to quantify.

So, if you’re in the business of dealing with people – and if you’re in business then this means you – there is both an art and a science to this. And in that overlap, there needs to be a fine balance, a creative intelligence, that starts with the science of data but only uses it as a foundation to make things more human.

Now if this is key for any Customer experience, it becomes more key as the interaction and the decision becomes more human, as the purchase becomes more considered. Wikipedia defines a considered purchase as, “a complex buying decision with a high degree of financial and/or emotional risk and reward.”  Emotion, risk, reward. Talk about human concepts that are hard to define in aggregate, nevermind for the ever diverse individual.

Industry studies tell us that 90% of decisions are based on emotions. Personally, I think that is far closer to 100%.  We make decisions every day based on emotion and justify them later. All these decisions require some degree of creative intelligence, of both art and science. And they involve some risk, some potential for loss. However, while buying a book is one thing, buying your first home, deciding on a cancer treatment, choosing a career, booking your honeymoon…these are quite another.  And it’s not just because of financial cost. With these decisions, these considered purchases, the risks transcend financial cost. There is more emotional skin in the game, sometimes to a very serious or life-changing degree.

For example, take the considered purchase of buying a home. Data may tell you how many times a person visits a website, what keywords or ads got them there, what pages they viewed, where they live, and a multitude of other invaluable information.  The science may find patterns and correlations between specific keywords and specific content or how demographics align with the length of time between research and purchase. But now you are left with the why? Why do the data yield those results? And in leveraging the human element, you put yourself in the shoes of the first time homebuyer who is about to start a family or empty nesters looking for a place to retire.  It’s those considerations that drive you to use science to make artful decisions on what to test and how to test it that are far different than the ones driven by data alone. That’s creative intelligence at work.

Therefore, while business intelligence is critical and artificial intelligence is powerful, there’s an argument to be made that creative intelligence leads the way for optimizing the considered purchase. If you think about it, it’s the only way to be truly Customer-centric.  How so? Because it’s the only way that gives the Customer, the human, the weight they deserve in the equation.

Creative intelligence for the considered purchase. That’s what it’s about now, or at least what it should be.

 

Key Takeaways:

  • The power of data can be used to fuel the customer journey from awareness to purchase to loyalty and evangelism. But data isn’t the whole story.
  • No matter how much data we have about our customers, this data is about humans—people with feelings and inclinations and needs that are challenging, if not impossible, to quantify.
  • Extracting valuable customer intelligence requires creative intelligence, a process that applies meaning and understanding to existing data.
  • Creative intelligence is particularly relevant to analyzing considered purchases— complex buying decisions with a high degree of financial and/or emotional risk and reward.
Category: customer intelligence
Shamir Duverseau

Maximize Data with Lean Thinking

Build. Measure. Learn. Those three words are at the core of Lean methodology, a way of doing business that incorporates elements from Six Sigma, agile development, design thinking, and other sources. Lean methodology is a modern application to business that has a longer history in the manufacturing industry, originating in the Toyota Production System in the 1950s. It has since been used by successful startups and large corporations alike, across industries. Lean’s continuous improvement cycle enables companies to make meaningful progress by getting the best use of customer data and intelligence.

When it comes to the digital experience, Lean thinking can be a tool of immeasurable power. From acquiring qualified traffic to converting those prospects into customers to retaining those customers to build lifetime value, a Lean viewpoint can help optimize every touchpoint of the customer journey. As this is especially the case in a considered purchase industry, Lean is now at the heart of how we at Smart Panda Labs are helping our clients drive customer lifetime value.

Here’s how.

Build

Everyone knows that building products and services that meet customer needs is a primary goal of any business. But customer needs are varied and nuanced, requiring answers to a long list of questions. If you wait to answer all the questions at once, or worse, assume you already know the answers, you risk high costs and wasted time at best. At worst, you risk the failure of an initiative, a division, or an entire organization.

This is why the term “minimal viable product,” or MVP, has become so popular and so important. A tenet of Lean and Agile methodologies, an MVP is a product with just enough features to satisfy early customers and provide feedback for future product development.  Each iteration of this streamlined product or service is meant to answer a question or two, or meet a set of demands, but not all demands at once.

We have learned the value of MVPs for our clients’ products as well as our own. So, we build new services and processes, not as fait accomplis, but as MVPs in order to ensure that are meeting client needs.

Measure

Objectivity does not come easily to modern day organizations. While gathering unbiased data is becoming easier, there remains a persistent risk of a biased interpretation of the data.

Lean accounts for this through customer-centric experimentation and measurement, allowing customer interactions and feedback to live at the center of the story. Actionable metrics inform whether your customer is experiencing your product in the way you hypothesize, or if you need to pivot. Either way, customer data and creative intelligence are guiding your decisions, thus maximizing the results.

Our own actionable metrics include feedback from our clients. How do they feel our innovation is helping them? Is it making things easier or harder? Is it aiding them in meeting goals or communicating with teams? The answers to these questions, along with many others, will help us to know whether or not we are moving in the right direction. And these decisions can be based on real feedback, and not simply cool ideas that we fall in love with but bring no benefit to the client.

Learn

“If you cannot fail, you cannot learn.” Eric Reis, the author of The Lean Startup, makes this simple but important point. Not everything works out the way you envisioned. Lean tells us that with every failure comes a wonderful opportunity to learn and iterate. The key is to embrace the opportunity.

For example. One of our clients engaged us to run an experiment on their website. The first test we helped them run failed miserably and quickly. It was designed to be a quick win … but turned out to be far from it. However, the resulting learnings from this failure yielded another experiment that was impactful in both its effect on the business goals (adding seven figures of incremental revenue for the year) and the additional customer insights it yielded.

Failure can’t always be the primary concern. Whether or not we are learning from these failures is what matters. We use our learnings to improve products and services on behalf of our clients, and also to improve the client experience we provide. What makes us better at our jobs also makes for better relationships.

Build. Learn. Measure. This is the backbone of how we harness data and creative intelligence to help our clients drive value from their customers, and it is becoming the method by which we serve our clients, period. If you are reading this, you are more than likely someone’s client. Should you expect any less?

 

Key Takeaways:

  • Lean methodology is a continuous improvement approach that enables companies to make meaningful progress by getting the best use of customer data and intelligence.
  • A key tenet of Lean is the “minimum viable product,” or MVP, which encourages the release of a product with just enough features to satisfy early customers and provide feedback for future product
  • Lean also emphasizes customer-centric experimentation and measurement, so that customer data and creative intelligence are guiding decision making.
  • Lean tells us that with every failure comes a wonderful opportunity to learn and iterate. The key is to embrace the opportunity.
  • As applied to digital marketing strategy, a Lean viewpoint can help optimize every touchpoint of the digital experience—from acquiring qualified traffic to converting those prospects into customers to retaining those customers to build lifetime value,
  • Lean and its backbone of Build, Measure, and Learn is now at the heart of how we improve products and services for clients. It also informs how we improve the overall experience we provide our clients.
Category: customer intelligence
Shamir Duverseau

Data, Diversity, and Design

In his best-selling 2005 book Blink: The Power of Thinking Without Thinking, Malcolm Gladwell’s discusses how humans think without thinking. Choices that seem to be made in an instant—in the blink of an eye—actually aren’t as simple as they seem. 

How does this process impact the digital experience? Does diversity in design make a difference? What key role does design play in this process? And if so, how do we measure this and tie it to meeting and exceeding business goals? 

These were some of the questions we tackled earlier this month at the dmi: Diversity in Design conference in Washington D.C. Smart Panda Labs Co-Founder Cheryl Myers and I led a session on how design—in particular, design representative of diversity—can and should be informed by data gleaned from digital experimentation.

Rapid cognition and thin-slicing

We began our session with an anecdote Gladwell presents in his introductory chapter of Blink. In 1983, an art dealer named Gianfranco Becchina approached the J. Paul Getty Museum in California claiming to have a marble statue known as a “kouros,” dating from the sixth century B.C. Becchina’s asking price for the statue was $10 million. The Getty took the kouros on loan and began a thorough investigation to authenticate it. From scientific evidence of its age to the bevy of documentation of the statue’s recent history and provenance, there was ample proof of the statue’s authenticity. The Getty concluded its investigation and agreed to buy the statue.

The kouros went up on display, receiving glowing reviews. However, the statue did not look right to a few people – namely an Italian art historian Federico Zeri (who served on the Getty’s board of trustees), Evelyn Harrison (a foremost expert on Greek sculpture), and Thomas Hoving (the former director of the Metropolitan Museum of Art in New York). They were each taken to the see the sculpture, and in what seemed like an instant, they all came to the conclusion that there was something off about the sculpture. All concluded that it was a fake.

The Getty launched a further investigation and found inconsistencies in the documents that supposedly proved the kouros’ provenance. It discovered that the statue actually most resembled a forged kouros that came from a workshop in Rome in the early 1980s. It turned out that dolomite could be aged in a matter of a few months using potato mold. The sculpture was indeed a fake.

“When [the art historians] looked at the kouros and felt an ‘intuitive repulsion,’ they were absolutely right,” writes Gladwell. “In the first two seconds of looking—in a single glance—they were able to understand more about the essence of the statue than the team at the Getty was able to understand after fourteen months.”

At the heart of Blink is the concept of rapid cognition, or “thin-slicing,” the process by which people make quick assessments using a limited amount of evidence. For better or worse, a staggering number of our decisions result from thin-slicing and instinctive hunches about how to act. While the conscious mind is good at studying a wide range of evidence and drawing conclusions from it, our “adaptive unconscious” is adept at assessing a very small amount of evidence about the external world—a “thin slice”—and then forming an instinctive response.

Gladwell is clear in the fact that rapid cognition is often imperfect and sometimes dangerous. After all, this how many prejudicial decisions are made. However, he argues that rapid cognition plays a valuable role in human behavior—a role that’s too-often ignored.

Designing with diversity in mind

As part of a firm specializing in optimizing digital experiences, my colleagues and I must be keenly aware of the rapid cognition and thin slicing that happens as a very natural part of digital engagement. Just as the art and antiquities experts brought their own expertise and personal experiences to bear in their snap judgment of the kouros, consumers are similarly informed by their own knowledge and experience when they interact with a brand’s website, for example. Everything about us, including our ethnicity, gender, geography, and age affect our world view. In our digital exchanges, we must be aware that the impressions made on users may not be the effect intended.

So how does this understanding of human cognition square with our roles as designers and digital strategists? And what do brands and businesses need to bear in mind? Just as our workforces need to be diverse and inclusive in order to better reflect the perspectives of our audiences and consumers, so should our digital experiences reflect the realities of those for whom we are designing.

During our session at the dmi conference, we shared a series of stock photos and website landing pages and asked our audience to share their impressions. The exercise helped to embellish upon our previous discussion on thin-slicing, and it also demonstrated the fact that diversity is relative.

What is diverse to someone from a rural and perhaps less racial diverse area of the country or the world is markedly different from someone from an urban center teeming with diversity. How do you balance such relativity with a desire to make design as personal as possible?

In pursuit of digital experiences that resonate, be data driven

What we see matters. But the question is, how much? Instead of making assumptions about your users, think of yourself as a student of the digital experiences you provide.

Experimentation, testing, and choosing a “learn-it-all” mindset over a “know-it-all” one (see Stanford psychologist Carol Dweck’s best-selling book, Mindset) is winning at some of the largest and most successful companies.

Take Microsoft CEO Satya Nadella, who recently said about the mindset he is implementing at Microsoft: “Some people can call it rapid experimentation, but more importantly, we call it ‘hypothesis testing.’ Instead of saying ‘I have an idea,’ what if you said ‘I have a new hypothesis, let’s go test it, see if it’s valid, ask how quickly can we validate it.’ And if it’s not valid, move on to the next one.”

Or Amazon founder Jeff Bezos, who says, “Our success is a function of how many experiments we do per year, per month, per week, per day.”

Or Mark Zuckerberg, who said of Facebook, “One of the things I’m most proud of, and I think the key to our success, is this testing framework we’ve built.”

If you want to understand to what degree diversity plays a role in the products or services you’re offering, test it, and let the data reveal the answer. For example, change the images on your site to demonstrate differing kinds of diversity, such as gender, ethnicity, age, ability, and intersectionality—overlapping aspects of social categorizations—as much as possible. You may also want to highlight ADA compliance, as another example. Facebook data may be helpful to you in terms of understanding some of the interests and perspectives of your target audiences, and you can consider including some of that content on your site. Throughout this process, we recommend keeping your key performance indicators (KPIs) top of mind and maintaining authenticity—your goal here is to surface diversity without being disingenuous.

Now it’s time to put your efforts to the test. Here are the five steps we suggest in the experimentation process:

  1. Define your audiences
  2. Consider what diversity is for each audience
  3. Test—A/B testing, focus groups, and usability labs are all examples of types of test
  4. Read reactions, not explanations (think “adaptive unconscious” vs. conscious)

On this latter step, the point I am trying to make is that a user’s initial reaction, in the form of a rating, for example, is more useful data respective to a digital experience than a conscious explanation; that instant reaction more closely mirrors how decisions are made in such a context. In Blink, Gladwell shares examples of how this works in other contexts as well.

The impact of the changes you are testing can be measured in many ways, such as overall satisfaction (feedback, surveys, net promoter scores), site engagement, social media engagement, and conversion rates. Analyze the data to see if changes you’re making to your digital experience are moving the needle and helping you meet your KPIs.

Then, use your findings to evangelize the value of diversity throughout your organization.

KEY TAKEAWAYS

  • Rapid cognition plays a valuable role in human behavior and has a lot to do with how consumers experience digital. “Thin slicing” happens as a very natural part of digital engagement.
  • Everything about us, including our ethnicity, gender, geography, and age affect our world view. In our digital exchanges, we must be aware that the impressions made on users may not be the effect intended.
  • If you want to understand to what degree diversity plays a role in the products or services you’re offering, test it, and let the data reveal the answer.
  • The impact of the changes you are testing can be measured in many ways, such as overall satisfaction (feedback, surveys, net promoter scores), site engagement, social media engagement, and conversion rates. Analyze the data to see if changes you’re making to your digital experience are moving the needle and helping you meet your KPIs.
  • Just as our workforces need to be diverse and inclusive in order to better reflect the perspectives of our audiences and consumers, so should our digital experiences reflect the realities of those for whom we are designing.
  • Use your findings to evangelize the value of diversity throughout your organization.
Category: customer intelligence
Alex Corzo

Salesforce is Getting (Even More) Personal

Several of my colleagues and I recently returned from the 2018 Salesforce Connections conference in Chicago — an outstanding event focused on supporting connected customer journeys. There were dozens of sessions designed to help digital marketers better understand how to how to create personalized experiences at every touchpoint, specifically in light of constantly evolving technology and the new ways in which customers interact with devices (you can read some of our takeaways here). The conference was also an exciting opportunity to learn about many of the upcoming changes for the Salesforce 2018/19 roadmap, including a partnership with Google and the introduction of Interaction Studio.

Salesforce Connections Conference

Friendly Giants

In his keynote address, Salesforce President and Chief Product Officer Bret Taylor announced data integration between two giants of the cloud — Google Analytics 360 and the Salesforce Marketing Cloud. New Google Analytics 360 integration will evolve the capabilities of marketers to ingest analytics information into their Marketing Cloud journeys, and consumer insights from both Marketing Cloud and Google Analytics 360 will be brought together into a single analytics dashboard (inside Marketing Cloud). Conversely, Marketing Cloud data will be viewable inside Google Analytics 360 for attribution analysis and also to empower Marketing Cloud information to deliver more customized web experiences.

Salesforce President and Chief Product Officer Bret Taylor announced data integration between two giants of the cloud — Google Analytics 360 and the Salesforce Marketing Cloud.

Also in the pipeline (a beta version will be available later this year) is the ability to create audience segments, such as loyalty members and abandoned browsers, in Google’s Analytics 360 before connecting with those audiences within Marketing Cloud. “For the first time ever, audiences created inside the Google Analytics 360 platform can be activated outside of Google, in the Marketing Cloud,” explained Taylor.

Relevant Experiences in Real Time

Taylor further announced the official launch of Interaction Studio, a new Marketing Cloud solution that enables companies to deliver contextually relevant experiences in real-time across their channels. The introduction of Interaction Studio will change how marketers evaluate cross-channel messages to see a holistic view of when and how customers are interacting with a brand to deliver unique messages based on key moments that matter most to customers. With Interaction Studio, marketers can now see, track, and manage consumer experiences in real time from multiple channels.

This new solution continues to evolve personalization by integrating data and platforms that were once siloed and allowing marketers to better anticipate, predict and act on customer patterns. Interaction Studio will make it easier for marketers to translate those insights into timely and relevant communications.

Bigger and better things are on the horizon with Salesforce that take customization and personalization to the next level. At Smart Panda Labs, we will be using these tools to help clients provide the personal touch and instant gratification their customers now expect.

Key Takeaways

  • New Google Analytics 360 integration will evolve the capabilities of marketers to ingest analytics information into their Marketing Cloud journeys.
  • Consumer insights from both Marketing Cloud and Google Analytics 360 will be brought together into a single analytics dashboard (inside Marketing Cloud).
  • Marketing Cloud data will be viewable inside Google Analytics 360 for attribution analysis and also to empower Marketing Cloud information to deliver more customized web experiences.
  • Also in the pipeline is the ability to create audience segments in Google’s Analytics 360 before connecting with those audiences within Marketing Cloud.
  • The introduction of Interaction Studio will change how marketers evaluate cross-channel messages to see a holistic view of when and how customers are interacting with a brand to deliver unique messages based on key moments that matter most to customers.

 

Category: customer intelligence
Jessica Porges

What Digital Marketers Can Learn from Amazon’s Purchase of Whole Foods Market

My kids are back in school, and Amazon just closed their deal to buy Whole Foods Market. What do these events have to do with one another, you ask? A lot.

As with all things Amazon, their focus is on me—the customer—and my experience. The more they know about me, the more relevant my experience with them becomes. To that end, enter Whole Foods Market.

The tech giant’s $13.7 billion purchase of Whole Foods has sent shock waves through the grocery industry and suspicions among Whole Foods loyalists who have concern about how their shopping experience—or the quality of the products they love—might change. But so far, the takeover has been all upside for consumers.

According to Bloomberg.com, Amazon spent its first day as the owner of a brick-and-mortar grocery chain cutting prices as much as 43 percent. In the coming weeks, the Whole Foods rewards program will be rolled into Amazon Prime for added savings and in-store benefits. This affords Prime a valuable new perk to attract subscribers and will encourage Whole Foods shoppers to buy more—according to a survey by Morgan Stanley, 62% already have a Prime account. And 1010data found that Prime members have deeper pockets at Whole Foods than non-members, spending an average of $306 more over a 12-month period.

Of course, as I eluded to, the strategic implications of Amazon’s purchase of Whole Foods go much deeper—the acquisition offers its buyer a lot more value than the margins on organic avocados and rotisserie chicken. I’m talking about data.

Take an (Amazon) journey with me

Amazon already knows that I’m likely a mom of young children based on the diapers I order, the shows and movies we stream, and the parenting books I buy through my Prime membership. They also know I’m busy and seek ways to make my life more efficient, e.g. the Instant Pot pressure cooker I purchased. And now, if I shop at Whole Foods and use my Prime membership to get in-store perks and discounts, they will also be able to track my offline grocery store behavior and tie it all together. With massive amounts of data from Whole Foods shoppers, Amazon will ultimately be able to tailor the grocery shopping experience—and much more—to the individual.

Let’s pretend for a moment I didn’t own that Instant Pot just yet. Maybe I had just stalked it a few times online (since everyone is talking about them). Amazon might send me one of their high-converting emails promoting the Instant Pot, maybe with same day delivery (in some areas). They might kick in some trending one-pot recipes for beginners, with a list of ingredients I could also order and have delivered to my doorstep by upgrading to AmazonFresh.

The Amazon email I received after checking out the Instant Pot.  You can easily see how it would make sense to include recipes. 

Amazon’s goal is to make it so easy for me to get my groceries from them that I continue to do so (as opposed to shopping at the other grocer to which I’ve been loyal my entire life). They can send me weekly emails with Instant Pot recipes and links to order the ingredients. Maybe they’ll even upsell me on some Instant Pot accessories, like silicone fingertip mitts and that popular glass lid.

But they’ll also be able to learn what perishables I buy each week (because we never seem to have enough yogurt drinks or string cheese for my kids), automate it for me so I don’t have to even think about writing out a long grocery list, and deliver the food to my door (or have it ready and waiting for me in a locker at Whole Foods).

Amazon is a master of the upsell, using a highly sophisticated algorithm to recommend the right products to the right customers, at just the right times. Their treasure trove of data enables them to analyze behavior from customers and use this information to recommend products to those shoppers as well as other shoppers with similar profiles. The company has integrated recommendations into nearly every part of the purchasing process from product discovery to checkout.

They also dole out recommendations through email. Did you know that Amazon’s email marketing program analyzes the success of various campaigns and drives only the highest performing emails to a customer’s inbox? Smart. And now, whether shopping on Amazon.com or in Whole Foods retail locations, shoppers’ unique Prime identifiers are keeping track of all their activity, adding them to specific customer segments that can trigger personalized emails, messages on the website, retargeting ads and a multitude perks and offers.

How to think like Amazon

What can marketers learn from this tech behemoth with the potential to know everything there is to know about my movie preferences, lifestyle choices, kids’ snacking habits and my grocery aisle behavior? Regardless of the industry you’re in, your customers are engaged in a journey, and it’s your job to optimize the key decision points along their route with Amazon’s ninja-like precision. Here’s how to do it.

Map it out. List the key decision points along your customer’s journey and the steps necessary to take your desired actions. In my Amazon/Instant Pot example, that could include:

  1. Getting me to add the Instant Pot to my cart—ideally with add-ons
  2. Purchasing the Instant Pot
  3. Opening an email with groceries to buy from Whole Foods to make my first Instant Pot meal
  4. Adding those groceries to my cart
  5. Purchasing those groceries (either for delivery with the upsell to AmazonFresh or pick-up at Whole Foods)
  6. Subscribing to an auto-ship or weekly auto-order to pick up at Whole Foods
  7. Referring friends/family to Amazon Prime, AmazonFresh, etc.

Think about the metrics. Use analytics tools to determine a baseline for your online and offline metrics at the conversion points currently implemented.

Implement technology. You have data and you have a lot you want to do with it. Now you need the right technology to make it happen. Most of us don’t work for a company with the resources of Amazon, with several dozen people to build and optimize internal systems to power their customer experience. But, you can do the same with the right tool at the heart of your customer experiences.

For example, let’s talk about Tealium. Tealium has a suite of tools that allows you to gather data from various online and offline sources (Tealium IQ Tag Manager), slice and dice your consumers into segmented groups, and then share that with other systems both for action and analysis (Tealium Universal Data Hub). (You can learn more about tag management in our earlier post, 3 Tag Management Systems To Make Your Life Easier.)

Tealium allows you to ingest multiple data sources, stitch them together, and then push meaningful data into other systems to trigger actions or to analyze for insights.

If I’m looking at the Instant Pot but haven’t yet pulled the trigger, I’m placed in a group that will be encouraged to make the purchase via remarketing and retargeting tactics.

If I decide to walk into Whole Foods and pick out my groceries the old-fashioned way, I’m incentivized by perks to reveal my Amazon Prime membership and, when I do, my website activity and in-store purchases become tied to the same member number and united in Tealium.

From there, I can be put into another segment of customers, which may trigger certain personalization on the website that prompts me to share my experiences, sign up for perks and more.

It’s likely I fall under a few different marketing categories: “high disposable income”, “young children”, “healthy lifestyle”, “tech gadget lover”. Because Amazon doesn’t want to flood my inbox, they will choose the most successful of the emails that are relevant to me that week, e.g. “top toys for children” or “best newly released workout videos” to increase the odds of me opening it, clicking through and potentially converting.

Applying Tealium to your customers’ journey

No matter your industry, multi-channel analytics, personalization and re-marketing are your best digital marketing tools for driving conversions. Using a tool like Tealium enables you to tie customer data together and activate next steps. Let’s look at a few examples.

Hospitality

If available, I tend to stay at Ritz-Carlton hotels when I travel. When I book my room online, I log into my existing account and enter my member number to earn rewards. That gives Ritz-Carlton at least two unique identifiers to analyze my behavior and market to me in a more personalized way. Using a tool like Tealium, they can tie me to the types of rooms I’ve booked or upgraded to in the past from their CRM and tailor an “upgrade now and save” message to me.

Tealium then tells their email service provider (ESP), such as Salesforce Marketing Cloud (SFMC), to send me that message as part of my confirmation email, or it tells a personalization tool like Optimizely to give me this message on the confirmation page. Or, both—it can serve up the upgrade message on the confirmation page and, if I don’t react, include it in the confirmation email. Perhaps the message comes to me before I even book the room. If Tealium sees that I didn’t choose the upgrade in the booking funnel, it could tell a tool like Yieldify to inject a targeted message in the booking process. It could also learn from the CRM that I’ve dined at their hotel restaurants and tell SFMC to send me a pre-arrival email with available dinner times during my stay.

By targeting messages at key points in the conversion process, such as after a room type is selected, you can improve the customer experience and better meet your business goals.

Real Estate

Opendoor.com is a relatively new company that buys and sells homes in a streamlined fashion– they supply a seller with a firm offer within 24 hours that the seller either accepts or rejects. After Opendoor owns the home, they make any necessary updates or renovations and then list the home in their inventory online. Anyone interested in viewing the property can gain access instructions through their mobile app.

Let’s say I’m in the market for a new home, so I download the Opendoor app and set my search criteria. I go visit a few of the homes on my list, but none of them are the perfect combination of the features I want. As I leave each home, the app detects I’m leaving the area and sends a push notification to complete a short survey providing feedback on the home, perhaps using a tool like ForeSee. ForeSee then sends that information to Tealium. Did I love it, was it missing something? Tealium sends this data to Opendoor’s recommendations engine, to help make better recommendations to me (and others like me) to view other properties. At the same time, the data could even be combined with other data and sent to Domo, to help Opendoor analyze and select the appropriate features to look for in (or add to) the subsequent homes they invest in, getting close to a “just-in-time” model within the pre-existing real estate market.

Healthcare

As a mom of two kids, I’m a frequenter of Urgent Care. Perhaps at my most recent visit, I opted in to receive newsletter communications from the health system. These emails may contain general tips on staying healthy, but Tealium can help connect the ESP to the CRM so that the email could also be personalized based on what the medical center knows about my previous visits (being careful to mention that I’m simply an anonymous patient ID, not a name, by simply grouping me into a segment). If I click through one of these emails to the site, perhaps to read about yoga exercises I can do at home, Tealium can connect my urgent care visit to my website visit and to the content I viewed, all in the CRM. Perhaps after reading about yoga, I read about primary care physicians before leaving the site. Tealium can now tell the ESP to personalize a section of my next email with information about choosing a PCP, maybe even including a short list of physicians near my home.

Pressure cook your personalization

It’s been estimated that more than 80 million people are Amazon Prime members. With this data, it is capable of building analytic models which can predict what these consumers will want, how much they will want, and when they will want it. Now that Amazon can collect and connect data from offline purchases as well, the power of their customer insights is unrivaled.

Ok, so we can’t all be Amazon. But every digital marketer can optimize their business’s key performance indicators by understanding the customer journey and getting ahead of questions or roadblocks at each micro-conversion point. From there, you can use a toolbox of technologies and strategies to optimize the journey from consideration to purchase, and then help them to keep coming back for more.

Remember, it’s personal. Customers care more about themselves than they care about you. Use data to make your communications as customer-centric as possible. That’s what Amazon does best and a key reason for purchasing Whole Foods. Follow their lead and make the best possible use of the data at your fingertips.

Key Takeaways:

  1. The strategic implications of Amazon’s purchase of Whole Foods is less about brick-and-mortar retail or the margins on groceries. It’s about the data.
  2. No matter what industry you’re in, every digital marketer can and should optimize their business’s key performance indicators by understanding the customer journey and getting ahead of questions or roadblocks at each micro-conversion point.
  3. Tools like Tealium can help digital marketers gather data from various online and offline sources, slice and dice consumers into segmented groups, and share that data with other systems both for action and analysis.
  4. Remember, it’s personal. Use data to make your digital experiences as customer-centric as possible.