For every billion dollar idea there will be plenty that don’t add much to the bottom line and several that just eat up resources getting launched. More importantly, there will be many that reach the disagree and commit stage. The point is that most companies are consistently striving for innovation.
What if your team could regularly produce these type of ideas and you could implement and launch them with the agility that Amazon does? Is that a process you’d like to learn?
Jeff Bezos recently announced that Amazon has topped 100 million Prime members. Amazon Prime started just like every other idea in the nearly 2000 experiments Amazon runs in a year. Let’s spend a few minutes to understand their process and then look at how you can effectively adopt it as your own.
Every test begins with a team developing a 6-page narrative memo. No PowerPoint presentations are allowed.
We’ve also learned that what’s most important to the process is the perspective that these memos take. The keys to these memos are to write them from the point of view of the customer’s benefit and to start from the end result or the final goal. This is what Amazon calls “working backwards.” It’s what we teach as Reverse Chronology in our Buyer Legends process.
It may help to think of these internal memos as low-fidelity rapid-prototypes to keep your company agile.
When you start from the end-point and craft the narrative from there, you’re not tied to the present conditions, which means you’re not tied to optimize what already is, and you also build believability for what your idea could BECOME rather than starting from what it might be right now. Prime didn’t become a billion dollar idea overnight. And there were some challenges that had to be ironed out with it before it scaled as big as it did.
So if you started just with the idea to “test” this out, it wouldn’t have been a success.
You had to start with the idea that Prime Members became Amazon-exclusive with their buying and what that would look like and mean for the company, AND then you work backward on how to make that happen.
These documents are well-researched and carefully considered. They are intended to help others in your organization fully comprehend the recommended experiment, all logistics and the anticipated outcomes. Before a meeting starts everyone sits, reads these memos and add their questions in the margins.
These narrative memos align the organization and allows them to commit with the knowledge and resources to see the test executed. Keep in mind no team at Amazon is larger than two pizzas can feed. So there are thousands of teams developing ideas on a regular basis. How many of these ideas could your teams develop regularly if they had the tools and the skills to craft these memos?
We had the pleasure of developing our Buyer Legends Process in order to train Google’s teams to emulate this rapid, customer-centric, innovation process. Like all teams, they needed to communicate more efficiently, prioritize based on well-documented ideas and improve execution time and outcomes. They required a process to provide direct communication instead of implied instructions. Since developing the Buyer Legends Process to achieve those goals, we’ve used it to help dozens of companies from startups to existing brands to be like Amazon.
Would your company benefit from more customer-centric innovation, executing with greater precision & agility and developing a growth system like Amazon’s? Drop me a note if you want to chat further about this innovation process.
Are Personas Dead? According to a recent blog post on the Convince & Convert blog, they would have you believe they are.
Here’s why that’s wrong:
If I tell you “the king died,” that’s a single-event data point. Information, if you will. And if I tell you “the king died and then the queen died,” that’s two data points. It’s still information.
But if I tell you that “The king died and then the queen died of a broken heart,” that’s a story. I’ve taken the two data points and connected them with causality, which makes the data meaningful.
What does this have to do with Personas and Big Data?
All data records events. Little factual tidbits of what happened. At best, sophisticated analytics can record chronological records or patterns of events.
The website visitor did this. Then this. Then that.
Or, patterns: male customers tended to buy this instead of that.
But notice that the reported chronologies and patterns are absent causality and intention. A series of events for a Web or store visit remain nothing more than an itinerary. And a pattern remains nothing but a correlation. There is no visible cause-and-effect relationship. There is no underlying shopper intention, and no meaning recorded by the data itself. That all remains for the marketer to provide via interpretation.
Humans cannot transform data points to insight about causality, intention, and meaning. To do so they must turn the data into a story.
Stories with the buyer as the protagonist.
And “buyer as protagonist” is another way of saying “persona.”
Formal Vs. Informal Personas
Are we really saying that all marketers use personas and tell stories when interpreting data?
The data might be as straightforward as “the all-inclusive bundle is our most popular product,” combined with “A/B testing proves that a satisfaction guarantee boosted conversions by 30%” And the story might be as simple as “this category of buyer chooses the satisfaction-guaranteed, all-inclusive bundled option because of its convenience and promise of risk reduction.”
Yet as simple as that interpretation of the data is, it still represents the creation of a story centered around a character in the form of a buyer.
Unfortunately, because the creation of the buyer’s persona was implicit and ad-hoc, it was also under-developed.
And that’s where the problems come in.
The Downside of Implicit, Informal and /or Ad-Hoc Personas
So what’s wrong with letting one’s personas remain implicit or unconscious? After all, we process intuitively as we make sense of the data?
Short answer: Our Baked-In Cognitive Glitches.
We have two cognitive biases when we rely on ad-hoc implied personas: 1) We assume everyone is like us. They value what we value, they make decisions like we make decisions, and what appeals to us also appeals to them.
2) We work off of stereotypes and then engage in the fundamental attribution error. When we see someone doing something, we tend to think it relates to their personality rather than the situation the person might be in. Well-designed Personas help marketers avoid these cognitive biases. They show how a different temperament might engage in a different decision-making process. They look beyond stereotypical attributions to see the context. The most important reason to use well-designed personas is prediction.
With a well-designed persona like a TV character, you can predict how they’ll behave. Character explains a scenario better than demographic and even psychographic data.
For example, suppose a white, middle-aged, middle-classed, white-collar New Yorker found a lost wallet, stuffed with cash. What would you predict he’s likely to do?
Well, based on that, you’d have no clue, right?
There’s no way you can confidently predict behavior based on the demographics provided unless you assume that the person in question would do what you think a typical person would do. Which is to say what you’d do.
That’s exactly the situation with implicit personas that are usually drawn from demographics or based on our own intuitions of how we or typical person would behave.
Now, if instead of giving you demographics, I told you that George Costanza found that wallet…
Now you can picture exactly what Costanza would do, even though it’s probably not anywhere near what you — or even a typical person — would do in the same situation.
That’s the kind of prediction those properly designed personas bring to the table.
And when it comes to crafting and optimizing customer experiences, that’s all the difference in the world.
Increased Data = Increased Need for (Better) Personas
Data and advanced analytics don’t and can’t change our hardwired need for a story as a sense-making tool.
In fact, the more complex and unstructured our data sets become, the more robust our storytelling chops need to be to help us not only analyze, but make sense of that data.
The disadvantage of structured data is that the structure limits the answers you can pull from it. The advantage of structured data is that the structure suggests the questions the database is capable of answering.
So while unstructured Big Data presents greater opportunities for marketers, it also increases the burden of coming up with and framing the right questions to ask.
The better designed the persona, the easier it is to interpret the data as narrative. Personas help frame and ask questions about intent, motivation, and cause and effect. These questions can then be posed to the data sets for not only answers but insights.
This is the only way to move from having data to being able to use that data to increase sales, market share, customer loyalty, etc. Personas Increase Empathy and Move Marketing Past “Optimization” to Innovation Without personas, marketers can certainly optimize what already exists to a local maximum. You don’t have to generate deep insight into the customer to run multivariate tests on different alternatives to the established patterns. Different color buttons. Slightly different calls to actions, hero images, page layouts, etc.
But you also can’t move past optimization to true innovation without thinking seriously about customer drives, frustrations, motivations, etc. Great customer experience design requires empathy.
And for empathy to be predictive, it requires fully fleshed out characters with which to work, just like you experienced with the Costanza example.
Your mind can do either one of these things, but it can only do one of them well at any given time. A marketers ability to generate customer insights come to live while in emotional storytelling mode, but fall dead while in number crunching analytics mode. And vice versa of course.
The point is, good marketers need both sets of skills, as well as advanced, rigorous processes for supporting and exercising those skill sets.
No one would ever argue that marketers don’t need or benefit from accurate and advanced customer data. Or sophisticated methods of statistical analysis aimed at sifting and sorting through that data, looking for patterns.
But that same level of rigor and defined tool sets also need to be brought to the storytelling side of the equation. Meaning that implicit and ad hoc personas just aren’t good enough.
And the more context-sensitive the situation, the more important simulation through storytelling and the use of formally developed personas becomes.
In other words, personas aren’t in opposition to data, they are the other half of the coin. Personas are a contextual tool for making data relevant and actionable. They are a bridge to understanding customers at a human level.
Without this, marketers are doomed. Without well-designed personas, it’s difficult to focus on customer experiences, rather than just products, price points, placement, and promotions.
So are personas still relevant in an age of data-driven companies?
Not only are they “relevant,” they’re becoming increasingly necessary for survival.
The sales team is having a hissy fit. They proclaim we’re 11% ahead of goal and we’re in the slow season! Why are you making life more difficult for the sales team? This change project is unrealistic! None of our competitors do better than us! It’s not broken, why fix it?
There’s a disturbance in The Force.
Ten seconds into our call I hear that Chuck, our client who owns a thriving $28 million business, is shaken up. We’ve been working together for almost three years. It’s not the first time we’ve met resistance to what the organization calls The Customer Rules Initiative.
In almost three years we’ve rolled out eleven important changes and dozens of small improvements. The Customer Rules Initiative has helped our client grow beyond their expectations.
Chuck is second guessing his twelfth change. The pushback on this change project is almost as hard as the first project where we decided to put all the information a customer needed on the website. The sales team was in open rebellion. They couldn’t imagine why anyone would call if we answered all their questions online. They were wrong then, they’re wrong now. Being wrong is human, acknowledging it and pushing beyond it is hard.
How Do You Stay On Track?
My job is to remind Chuck why the Customer Rules Initiative matters. First I listen. I listen for about half an hour. This has the desired calming effect.
I remind him of his favorite quote: “There is only one boss. The customer. And he can fire everybody in the company from the chairman on down, simply by spending his money somewhere else.” – Sam Walton
Chuck is listening, that’s good. The problem is real. We have to fix it.
Chuck is committed to what we teach as The Four Pillars of Amazon’s Success:
Culture of Innovation
If you’re a growing company it’s hard to argue with any of them. Intuitively every business owner knows they need all four pillars, they are unifying principles.
Chuck’s the guy that pointed out that The Force that propels this flywheel is Customer Centricity. The gap between customer expectations and customer reality is what needs to inform change.
The Force = Customer Centricity = Caring about the customer’s perspective
What Caused The Disturbance In The Force?
After almost three years of continuous improvements, why don’t they just trust us? If it were only that simple.
We came up with the twelfth change the first month we engaged. We’ve been putting off taking action on it since then.
A few months ago while visiting with Chuck and his senior executives at an offsite retreat we needed to print out several documents. The hotel couldn’t accommodate us. Bryan, my business partner, ordered a printer using Amazon’s Prime Now. Less than an hour later we were printing.
Bryan decided to point at the elephant in the room. We can get a printer here in an under an hour, why exactly can’t the sales team always respond to an inquiry within two business days? What do your customers expect?
Sales Team Response Time
In our first draft of our Buyer Legend, the narrative originally read that the customer was delighted because sales team responded in four minutes. That draft was abandoned. Two business days was substituted. They didn’t know their actual response time but anecdotally we estimated it averaged 2-4 days. We didn’t win this battle but we did insist on compliance with updating Salesforce. We now know that they respond to 87% of leads within two days. Of course, there are automated emails that are intended to follow up.
Yet, customers are human. Humans want what they want now. Not later, not even in five minutes. We want it now!
A New Goal – 5 Minute Response Time
After a long discussion, we agreed to tackle the twelfth change. We agreed that customer expectations could be unrealistic but we could meet that challenge. It helped that this time we had internal data to back us up. Leads that were reached by phone the same day closed a little over 3x the leads that took more than a day to respond to. Leads are expensive! We also reminded them of The Lead Response Management Study by Professor Oldroyd, a Faculty Fellow at MIT.
The new buyer legend says: “John (the prospective customer) is delighted because the inquiry was responded to immediately. John says “if they respond that quickly to an inquiry I bet they do that for customers too.”
Let’s examine why this change makes sense based on the unifying principles of Amazon’s Four Pillars Of Success:
Customer Centricity – immediate response is what the customer wants and expects
Continuous Optimization – be better today than yesterday is always the way towards our new goal
Culture of Innovation – find solutions and embrace change to improve customer experience
Corporate Agility – work to become more nimble and react to changing customer expectations
The Sales Team Rebels
This change is what the sales team was up in arms about. They missed the part where the sales coordinator, a new position, made the call answered a few questions, asked a few questions to qualify the prospective customer and scheduled a follow up with a sales person.
What we had was a failure to communicate. Chuck assumed the sales team reread the Buyer Legend carefully. The did not. Crisis averted.
Publishing a new Buyer Legend means employees scan quickly for changes. There are always minor changes highlighted but major ones are deliberately not. That is supposed to encourage careful reading.
Disturbance In The Force A Post Mortem
There are four forces that pull against the unifying principles of Amazon’s Four Pillars of Success:
Maintaining Status Quo
We could call them disunifying principles.
Let’s examine how they almost derailed the twelfth change:
Organizational Focus – the sales team metrics were focused on their own team’s “performance”, not the customer
Maintaining Status Quo – the sales team didn’t perceive their process as broken
Competitor Focus – the sales team saw themselves relative to competitors but not relative to the gap in customer expectations
Misplaced Accountability – the sales team was exceeding sales goals, an internal benchmark, but that data didn’t reflect the customer’s reality
Happily Ever After?
The sales team was asked to reread the Buyer Legend and some minor edits were made and agreed upon. The twelfth change is underway and initial results are positive. We’re nowhere near the 5-minute goal but our motto is #BeBetterToday. Nearly every lead is having a conversation within the same day as their inquiry. The hero of a Buyer Legend is always the customer. Chuck is unshaken in his faith that when he takes the customer’s perspective things work out well in the long term.
Customer-centricity is like “excellent customer service” — everyone thinks they’re doing it, few actually are.
And one reason for that is that there are right and wrong paths to pursuing customer-centricity. Her’s a quick chart of the three most prominent wrong paths vs. their right path counterparts:
The first “wrong path” towards customer-centricity is taking customers’ (or worse, unqualified prospects’) spoken wishes at face value.
In other words, relying solely on surveys of potential customers as insight into “what the customer wants” is a bad idea. You might expend company resources creating exactly the offer people say they want, only to watch all the actual, paying customers actively choose someone else when it’s time to buy.
Businesses that achieve epic success through customer centricity take great pains to “see their customer real.” We’ll get into depth on techniques for this in my next post, but it involves tracking actual data on customer actions and understanding the context of buying decisions.
The second “wrong path” is to focus on the Peripherals at the expense of the “Hard Stuff.”
Imagine a dentist who focuses on being customer-centric by improving his waiting room with more comfortable furniture, a cappuccino machine, fast & free wi-fi, and plenty of power charging stations. That’s a focus on peripherals.
A focus on the hard stuff would be finding a way to reduce wait time to (nearly) zero.
The difference between peripherals and “hard” items is that
Peripherals change with the times, hard stuff does not, and
Hard stuff has the power to make peripherals irrelevant
The factors that make a better waiting room change with the times; for example, better magazines have given way to wi-fi. Whereas reduced wait time is always desirable, and a significantly shorter wait time makes the quality of the waiting room irrelevant.
The third “wrong path” is to over-focus on optimizing existing processes at the expense of re-engineering and innovation.
It’s a good thing to optimize the customer interactions you have in place now. But if you’re not looking at what customers really want — at an ideal interaction, unconstrained by current technology or operations requirements, — you won’t be able to innovate and invent on the customer’s behalf.
You could find ways to optimize the cash register or check-out experience for your store. by speeding up the check-out, keeping more registers open, automatically opening new registers when wait times exceed a certain number of minutes, etc.
Or, you could take advantage of new technology to re-engineer the shopping experience to render the cash register obsolete. Amazon Go‘s new offline store’s payment is handled via tracking and recording what you put in your cart and your card is automatically charged when you walk out the door with your stuff.
So what paths are you taking towards customer-centricity?
Customers are more connected than ever. Software continues to reduce customer friction everywhere, from customer service to fulfillment. Logistics and payment systems continue to expand what’s possible for customers. Customers expect more and better.
Retail customers aren’t delighted with retailers. They feel differently about Amazon and in both cases it’s the CEO’s fault.
All the above is true. It’s why CEOs green light new and growing investments in technology and marketing. So how can I say that retail CEOs don’t care about digital?
Digital is not just a series of new shiny objects, cost cutting tools or new media ads. Digital should be the glue that connects every part of the organization with customers. Digital should allow every part of the organization to analyze data, learn from it, and act on it. The competitive advantage is putting that customer at the center of their universe.
The top 25% of online retailers convert at 5.31% and the top 10% of online retailers convert at 11.45%.
Amazon Prime members convert 74% of the time on Amazon.com. That is according to a 2015 study from Millward Brown Digital. Compare that to 13% for non-prime members.
Amazon’s user interface isn’t 22x better than average. Amazon’s copy isn’t 22x better than average. Amazon’s design isn’t 22x better than average. Amazon’s prices aren’t 22x better than average. Amazon isn’t average and it doesn’t think about average conversion rates or average customers. Amazon’s stated goal is to be “the most customer-centric company on earth.”
This fits with how we define conversion rate. “Conversion rates are a measure of your ability to persuade visitors to take the action you want them to take. They’re a reflection of your effectiveness at satisfying customers. For you to achieve your goals, visitors must first achieve theirs.” We first wrote that in 2001 and it continues to be true.
The story you need to get right is not the story you tell you customers; that’s just promotion. Fix the story from the point of view of your customers. Because your brand isn’t what you say it is but what your customers say it is.
Amazon’s brand is demonstrably strong with their Prime Members.
You too can convert more. Try creating Buyer Legends for your brand in order to create a better customer experience. If you need help, please let us know.
In our experience hacks often fall short. They rarely deliver meaningful results or deliver insight that leads to the next high impact change. A clever or creative hack that doesn’t improve the customer experience is just a band-aid. Hacks are tactical, not strategic. SunTzu wrote: “tactics without strategy is the noise before defeat”
Tactics are not relevant to your customers’ needs they are just more noise. If a ‘hack’ fails to increase your conversion rate, it’s not because the hack was bad. It’s likely more strategic; you don’t understand your customers needs well enough.
Hacks can be useful if they fit into a strategy. In order for them to be useful, they need to add value to your customers’ buying experience.
Where do good hacks come from?
Would you like to find a treasure map with high impact conversion optimization ideas for your business? You don’t have to wait for some guru to figure it out for you. You can generate your own hacks based on customers’ needs, problems and buying styles.
“We have worked with companies of all shapes and sizes that possessed varying degrees of talent and competence. We have tried it all, training and encouraging our clients to go deep into the marketing disciplines as well as guiding them through adopting a very robust optimization process.
But what we didn’t know early on was how a single piece of that optimization process, what we at the time called scenario narratives, would reveal itself over and over as the ‘one thing’ that has the largest impact on a company’s ability to sell more.”
The ‘one thing’ is a simple process we have developed over almost a decade of our work. The Buyer Legend process provides you a treasure map that any competent marketer can create. They can then use that treasure map to improve their customer experience. That leads to conversion rate increases of multiples instead of increments.
The most powerful hack revealed
It’s not sexy. It’s not hip and edgy. Yet it works every time. Average marketers will often outperform others who are more experienced and talented.
Hack into your customer’s head. Uncover their needs and wants. Exceed their expectations. And then give them what they really want.
The simple process we developed to deliver on this promise is Buyer Legends. Buyer Legends will:
Help you to create real-world improvements in your customer experience.
It will take you about 2 hours. Then you’ll have a real treasure map of conversion rate optimization ‘hacks’ for your business.
Make a commitment
You’ll need to commit to providing a better customer experience. Focusing on conversion rate increases is not enough. It’s that commitment that requires true effort. There is no easy way to make a major impact, you always have to do the work. Trust me, it’s more difficult to be on the CRO hamster wheel. The status quo will continue to yield only incremental results.
We want to start a new conversation about the future of CRO. To survive it must evolve. We want to help marketers help their customers buy. We want to help marketers avoid irrelevant hacks. We want you to use this process and then tell the world about the results. It’s the only way to change narrative.
Every marketer struggles with managing resources. Most feel they are under-resourced to make the kind of impact they would like. You don’t have to stretch your resources to test out and prove this process works.
We have also eliminated the “I don’t have the time excuse.” Creating your first Buyer Legend will take you about two hours.
The Buyer Legend process in action
The first step of the process is to create a profile or persona of one segment of your customers. Next you will use the persona to brainstorm a premortem list. The premortem focuses on all the things that go wrong in their customers’ experience. The premortem list alone should provide several new ideas for relevant hacks. You can read more about all five steps of the process here.
For example, we recently wrote about a smart frugal persona (Marcy). This persona was buying a microwave online. In her premortem, we uncovered how Marcy researches prices. If Marcy feels like she can get it cheaper elsewhere then she won’t stop looking. She needs to know that she is paying the lowest price. Bob’s Appliance Outlet (not the real customer) is a high volume low margin business. They sell on price. Now observe in this part of her Buyer Legend how we addressed this specific need:
“…Marcy stumbles upon a website for Bob’s Appliance Outlet. A large banner on the homepage announces that most items qualify for free shipping. Even more impressive is a smaller banner in the top right corner of the page that says: “Want the lowest possible price? “Name your price” make an offer on any item in our store, and we will do our best to match it”. Marcy clicks on it. She reads the next page. She finds that the price offer feature is simple and straightforward. There is no fine print. She still wants to learn a bit more about the company and goes to the About Us page . After she reads this page she feels confident. This is a credible company with a credible offer. She then does a site search for the microwave she is looking for and finds it. She reads through the product description and reviews for due diligence. She is delighted. Her microwave qualifies for free shipping. Elated at the possibility of saving more than she expected, she enters an offer. It is $100 dollars under the lowest price she found elsewhere and hits the Buy button. A page comes back and tells her that her offer was too low but encourages her to try again. She didn’t think they would accept another offer, but felt it was worth a try. She enters a price that is $50 under the lowest price she found before. This time the offer is accepted. Marcy is presented with a page that congratulates her. It lets her know that her item will ship today. It asks her how she would like to be notified about shipping. It also asks if a text message is appropriate.”
This ‘name you own price’ checkout hack will be great for their Marcy-like customers. This is a great way to keep price scavengers from leaving their site without buying. Even with a phone number available, few prospective customers want to call Bob’s to haggle. Allowing Marcy to set her price is powerful. Of course, it’s all within the price parameters Bob’s sets in place.
You can give customer what they want
Going through the process and writing the Buyer Legend is rather simple and easy. Implementing this customer experience was a challenge. It was championed by someone in the C-suite. Fortunately, it was already described in great detail and that helped. It still took some testing to get it right for both the customer and the business.
Buyer Legends are measurable and accountable by design. That is one of the important elements that distinguish Buyer Legends from any other business-storytelling and customer experience methodologies. A Buyer Legend is not a feel good story; it’s about business, and if your story doesn’t improve on your business goals, then what is the point?
Your Buyer Legend should describe in significant detail what actions you expect your customer to take, many of which are measurable. Pages viewed, transactions, subscriptions, store visits, phone calls, conversions to lead, and even social media engagement are all measurable.
Not All Customer Actions Are Created Equal
But they can all be useful to your optimization. In 2011, Bryan Eisenberg wrote:
If you are in retail, you want them to purchase a product.
If you are in lead generation, you want them to become a lead.
Are there no other actions that are valuable and contribute to the bottom line?
In retail, even if they don’t convert now, would it at least be more valuable to know if they added an item to their wish list, or subscribed to your newsletter, or looked up your retail store hours, or added items to their cart versus just bouncing off the site right away? What are you doing to turn that one-time customer into a repeat customer? Do they only need one product you sell or might they need different ones over the course of time?
In lead generation, if they don’t give you all their information and request to be contacted by sales, is it valuable to have them sign up for a whitepaper, or a demo, or your newsletter? Is it better to download specification sheets, engage in calculators, or print/forward pages rather than just bouncing off the website? These are all steps that move people through their buying process.
These are just some of your macro actions. What happens when someone comes from one of your ads and gets to a landing page? Sometimes the action is one of those listed above, but what if that page is only meant to help your visitors to choose the right product or service and they still need to actually click on the right one for them? What do you do to help them take that action and not bounce away? These are the micro actions that need to happen from step to step in the potential customer’s journey.
All of these are actions we need to optimize. You can calculate a conversion rate for each one of these macro and micro actions, and you should.
I wrote in a recent Buyer Legend Recipe Series post about persuasive momentum that whether or not you are aware, your business has created a de facto persuasive system. Buyer Legends is a process for creating a persuasive system that is intentional, measurable, and optimizable. That is why it is important for you to track both the micro and macro actions so that you are not just optimizing the final conversion, but all the steps in between where you can spot breakdowns in the system and fix them. Buyer Legends, done right, allow you to measure and optimize persuasive momentum.
While it is much easier to track and analyze online behavior, technology is making it possible to track and analyze in-store traffic as well as in-store behavior.
Your hero is on a journey. You tell his or her story. Every successful customer journey needs a map and every map needs a legend. The journey’s legend is the key to navigating the map. See below the components of a legend.
Hero – This is the protagonist of your legend. All legends are told from the point of view of the hero.
Catalyst – This is the point at which the customer first identifies your company, product and/or service as a potential solution. It can be word-of-mouth, on- or off-line advertising, or PR. A catalyst can be a measurable step in the customer’s path, but often cannot be attributed to just one thing.
First Measurable Step – Here is where your customer enters the measurable portion of the journey. It can be finding a landing page, home page, chat session, phone call, or brick and mortar visit.
Road signs – Some points in the customer’s path that are critical to their completion of the journey. Road signs include information that, if not available, will most likely prevent the customer from completing the journey and/or keep the marketer from persuading the customer to make a decision necessary to continue the journey.
Detours – These are pathways that marketers must construct as solutions to forks in the road. Customers don’t always go straight down a smooth sales path. They often go off the path in search of answers to concerns, alternative solutions, or just plain curiosity. When this happens, the potential exists for that customer to never arrive at the desired destination. They took that “left turn at Albuquerque” and never got where they wanted to be. Detours meet the customer along those wrong turns/paths and guide them back onto the proper path so they can continue the journey to their destination.
Measurable step – Any step along the way that can be measured. Typically, this involves analytics, but it is any step a customer can take that leaves behind evidence of that step. Measurable steps give insight as to where customers are in their journey and how they can be optimized.
Fork in the road – These are decision points in the persona’s path where a specific need or curiosity can take them off the ideal path in search of answers to a specific need, curiosity, question, or concern. Because the marketer should never force a customer down a path, awareness of where a customer could go “off-track” becomes crucial, so that the marketer can plan for these forks in the road and construct detours that will take them from an undesirable direction back onto the desired path.
Destination – This is the final measurable step where the customer converts into a lead/sale, completes an order, a form, or a task.
In the three examples that you’ll find at the end of this post, you’ll notice the legends are in parentheses.
Understanding the Value of Quantitative vs. Qualitative
We recently worked with a large data-driven technology company that had no shortage of quantitative data. In fact, they sent us gigabytes of it. We noticed that for every ten quantitative reports there was only one qualitative report. It was obvious to our team that their bias for hard data left them with a huge blind-spot. Quantitative data tell you WHAT your customers are doing, and qualitative data can provide insight into WHY your customers are doing what they do. They pointed out a problematic metric to us and asked us our opinion. A significant portion of new customers were using their software service once maybe twice and then falling out. We began a simple qualitative research exercise, we visited their sales call center and listened in on a several dozen calls. Soon the quantitative data began to make sense. We found that this company had such a strong brand that most people simply trusted the brand, so they signed up only to find that after using the software it wasn’t exactly the experience they expected. We couldn’t fix the software, so we solved the problem by helping them provide customers with the correct expectations in advance.
As human beings, our actions can be measured. This creates quantitative data. But the thoughts, emotions, and decision-making styles we use are subjective. They do have some degree of predictability, and this is qualitative. A business needs both types of research to see the whole picture. So, do not discount the value of focus groups, surveys, customer interviews, and even customer comments and reviews as you begin to craft your Buyer Legend.
Amazon is a great example of a company that uses both qualitative and quantitative. Never accused of being a warm and fuzzy guy, Jeff Bezos set Amazon on a course to be “the most customer-centric company on earth”. That involves not just knowing what customers are doing, but trying to understand why. Bryan Eisenberg wrote about Amazon’s Performance Secrets:
When Bezos decided to launch Amazon.com in 1994, he realized that the unique advantage of the Internet was the ability to programmatically learn more and more about your customer and personalize their experience. He realized that they could leverage every bit of data correlated with their customers’ personal unique identifiers (their email addresses) from each and every interaction. Amazon could learn from every sale, but also from every click, review, and mouse movement.
I suggest you read the entire article.
Thank you for reading this last post recipe series. Our goal was to supply you with more in-depth information that you can lean on as you proceed with implementing Buyer Legends. If you have questions that arise as you work on your Buyer Legends, please send them our way and we’ll try to answer them.
P.S. This is the sixth and last in a series of six Buyer Legends Recipe posts, please sign up to our newsletter for updates.
Three Examples of How To Measure Buyer Legends
Example #1 – an e-commerce Buyer Legend:
Marcy (hero) is frustrated that her microwave has broken (catalyst), so she moved it up on her to-do list to research and order a replacement today. She visits a handful of consumer sites, reads reviews, chooses the features she wants, lists a few possible models, and then measures the space in her kitchen to ensure that she doesn’t order a microwave that is too big or small. With measurements in hand, she is able to knock a handful of models off her list, leaving her with three choices. She goes to BestBuy.com, Sears.com, and Amazon.com to see more pictures, read more reviews, and compare prices. She notices that Best Buy has a price match guarantee but she will have to jump through too many hoops. Marcy is resourceful and frugal, and believes she can find the absolute lowest price for the microwave she wants. She does several Google searches, and visits a few sites but she is not impressed. The sites look unprofessional and the prices are all about the same.
Then, Marcy stumbles upon a website for Bob’s Appliance Outlet (measurable step). A large banner on the homepage announces to Marcy that most items qualify for free shipping (road sign), but even more impressive is a smaller banner in the top right corner of the page that says, “Want the lowest possible price? Make a price offer on any item in our store, and we will do our best to match it” (road sign). Marcy clicks on it (fork in the road), reads the next page and finds that the price offer feature is simple and straightforward with no fine print. She still wants to learn about a bit more about the company and goes to the About Us page (detour). After she reads this page she feels confident that this is a credible company with a credible offer. She then does a site search for the microwave she is looking for and finds it (measurable step). She reads through the product description and reviews for due diligence. She is pleased that her microwave qualifies for free shipping. Elated at the possibility of saving more than she expected, she enters an offer $100 dollars under the lowest price she found elsewhere and hits the Buy button (measurable step). A page comes back and tells her that her offer was too low but encourages her to try again. She didn’t really think they would accept another offer, but felt it was worth a try. She enters a price that is $50 under her previously lowest price, and this time the offer is accepted (destination). Marcy is presented with a page that congratulates her and tells her that her item will likely ship today and asks her how she would like to be notified about shipping. She chooses text message over email or automated phone call. Marcy goes to the kitchen satisfied, and pours herself a cup of tea, She crosses Find New Microwave off her to-do list, and begins the next item on the list.
Example #2 B2B lead generation Buyer Legend:
Mark (hero) is a savvy entrepreneur who is looking to expand by opening up a 4th location in the greater Phoenix area (catalyst). Mark used some pricey consultants in the past with mixed results. Someone told him about Idealspot.com so he went to the homepage (first measurable step), and when he saw the word algorithm, he immediately lost confidence. Mark simply believed that an automated computer process could not possibly find him a great location, so he leaves and forgets about Idealspot.com (detour).
A week later Mark is on LinkedIn and sees a ‘re-targeted’ ad with the headline, “How Science and Big Data Are Changing the Way Businesses Choose New Locations”. Not recognizing this as a post from the Idealspot.com blog, he is intrigued and clicks through (measurable step). He reads about how big data is able to spot success patterns. It explains that most location analyses hit the wall when people become involved in spending time and money collecting piles of data, but then have no way to relate it to the success or failure of their business. This is where big data and learning algorithms inject science into the process by mining through the data to pick out those patterns of success or failure and the key factors driving those patterns. The algorithms act without human bias; they start from scratch and come up with a model that is unique for each business based purely on results. Mark is starting to understand the value of Idealspot.com; he had assumed that human involvement was superior, but now he began to doubt that premise. Mark clicks through to the Idealspot.com How Does it Work page (measurable step).
Mark reads about the algorithm and how the data is loaded for each location, and how the success-prediction clientele are chosen, based on competitors and his type of business. He sees this is similar, even superior, to the methods used by much more expensive location-research alternatives. Mark starts to feel excited.
Mark wants to get a sense of the Idealspot.com track record, so he clicks on the Success Stories page (fork in the road) and reads a handful of stories by clients who are experiencing early success. He sees that Idealspot.com is a startup and their term track record is not as long or established as it could be, but the low introductory price of $297 removes this barrier from his mind.
Mark wants to try Idealspot.com. Still believing the pricing is too good to be true, Mark reads a section on the Pricing page (detour) that explains how big data and learning algorithms dramatically reduce the cost of research allowing IdealSpot to offer high-value analyses and rock bottom prices (road sign).
He clicks the Get Started button (measurable step). It explains the cost of each report, and that he is setting up an account that will allow him to enter potential locations and request as many or as few reports as needed. He does not need a credit card right now.
Marks appreciates that his privacy will be protected.
Mark fills out a form requesting his name, email and password, and then clicks Join and creates an Idealspot.com account (destination). He is excited to start scouting locations and using Idealspot.com for feedback.
Example #3 B2C multi-channel Buyer Legend:
When Debbie (hero) turned 12, her Aunt Rebecca bought her a charm bracelet with a collection of charms. Debbie loved it, and 29 years later she still wears it. And now her 11 year old daughter Ashley is coming up on a birthday. Ashley loves her mom’s charm bracelet, and is always looking through the charms and asking questions. She even asked to borrow it for a night out with a friend. Debbie of course wants to surprise her daughter on her birthday with an impressive bracelet and nice collection of charms to get started (catalyst).
While out and about running errands she takes a moment to search Google on her Android phone for “Charm Bracelets nearby”. Of course, she sees Pandora at the mall but thinks they are overpriced. She also finds a Charm Boutique and decides to drop by to see what they have. As she walks in (first measurable step) she is is greeting warmly and encouraged to take her time look around and then just ask if she needs help.
Debbie is impressed with the store; their oversized charms hang in the windows and from the ceiling. It is a fun atmosphere, where she can imagine returning with her daughter and buying new charms in the future. As Debbie scans the merchandise under the glass she sees several bracelets, none of which she think would match her daughter’s taste. She asks if they have any more styles and the saleswoman takes her to a computer and shows her several more designs that are available online or by special order (road sign). She zeroes in on a style and asks about it. The sales woman tells her that it is on back order and it may take several weeks to Special Order, but that it may be available online. Debbie asks her to please write the model and style number down for her and then turns her eyes to the charms. They have an impressive collection but she can’t find a couple of essential charms she would need. Ashley and she share a love of folk music and spend a few evenings a month playing guitar and singing, so a guitar charm is a must. Ashley also loves and collects zebras but the store has none of those, either. While there, she picks up a handful of charms that Ashley would love (measurable step) and heads home (detour).
That night after Ashley falls asleep Debbie goes online to visit the Charm Boutique website (measurable step) and quickly gets lost in the selection. She finds the bracelet she liked at the store as well as a guitar charm, a zebra charm, and about a dozen others that she adds to her cart, satisfied she has found the perfect Birthday gift for Ashley. She hits the checkout button and sees the total. It’s a little more than she wanted to spend. So Debbie visits the Pandora website to compare charms and pricing (detour). She finds that many of the charms she wants are there, but not all, and the bracelet choices are not that great. Even more so when she places them in her cart and hits checkout. The price is much more than that of Charm Boutique. So, she goes back to the Charm Boutique site, and finds something she missed before. She sees that her order qualifies for free priority mail shipping and she could have it in a week, giving her plenty of breathing room before Ashley’s birthday. She finishes checking out and is tickled that this worked out so well. She can’t wait to see the look on her daughter’s face when she opens this present.
P.S. This is the sixth and last in a series of six Buyer Legends Recipe posts, please sign up to our newsletter for updates.
As always, we encourage you to try Buyer Legends for yourself, but if you need help, please let us know.
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