Your CRM is often seen as a database by most. I see it as an extension of the human language. It is something to be appended with theories of people (The Clayton Christensen application of a theory, please). The only way this can happen is if you append not just the obvious data sets but create new ones that are 3 and 4 chess moves out. Most people are still trying to clean the address fields. I think it is time to own the CRM as the heart of the company. Not just the CRM as it is defined today but a future state CRM that includes the entire US CRM.
Time to step back: One area of focus for me has been the study of the Lexical Hypothesis. Also known as the Sedimentation Hypothesis, it has its recorded origins in 1884 by Sir Francis Galton. His book, Measurement of Character begun the long and somewhat long path to personality characteristics and language usage.
The Lexical Hypothesis is defined by two key postulates:
personality characteristics that are important to people will eventually become part of their language
the most important personality characteristics are likely encoded into language as a single word.
Research on this subject was slow as computing power did not exist to scale the research. It took some 50 years before Gordon Allport et al created a psychological classification of words. By combining this work with trait theory, one can begin to approach a classification system at scale.
Most input today on who we sell to comes from things that are generated with our hands. Clicks and cookies and past sales data really don’t tell the story of ‘why’ we bought what we did. It only records clicks. In a mobile world, click data mixed with desktop data becomes a mixture of conflicting stories. My point: we have bad data going into our CRM that feeds a stunted story to business leaders and marketing.
By studying personality characteristics without actually speaking with customers or violating their privacy, I found a way to connect the language people are comfortable with, the language in their daily life to a calculated personality type to CRM and look-a-like. I use Myers-Briggs but have also used temperaments, first studied by Hippocrates. It has evolved and to its current state by Dr David Keirsey, who calls it Keirsey Temperament Sorter (KTS-II). I also suggest that a conversion key does exist between DISC, Big 5 and MBTI but only for the purposes of growing a business. Our research at MakeBuzz has lead us to looking at personality of entire cities and States but not connecting this to a CRM is of no interests right now.
I would argue that because the data is now available, computing power, speed and capacity make this possible only today. Most research could only be produced at small levels, just like a focus groups always works from the lens of constraint.
All of this would be just research if you did not connect it to CRM. That is where you come in. By connecting calculated personality to what people buy, you see a source of truth that gives valuable ‘markers’ as to why people buy, why they desire and why customer expectations does not need to wait for purchase decisions. This work begins to validate the original research that dates back 132 years.
I invite anyone interested in personality, trait theory, CRM and customer intelligence to connect with us. It has been a desert. When you bump into someone, ask them for water. The good news, media is no longer cheap or that effective when it comes to filling a CRM, so now is the time to start from an entirely different and powerful direction.
We’re not trying to brag. It’s true! And we can make your CRM bigger by attaching it to ours.
Our technology can predict the personality of almost all Americans that spend money. So what?
By appending your CRM with the data in our CRM, we can show you some amazing things. More importantly, though, we can show you traits, desire and expectations about groupings of people, what they care about, and what they’re likely to buy in the future.
We discovered personality is the biggest differential in conversion rates. We have seen 30x difference between an ESTP and an INTP (for one brand, it’s totally different for you, most likely). Why that happens is hard to explain just like why some people get along and others don’t.
Here’s a hint: What people buy a year from now has little to do with what they bought in the past and everything to do with who they are. A year from now, what will you buy? Right! Click and cookies struggle but a theory of who that person is will not. Coupled with a client CRM, the ‘guide rails’ will create a subset of desire (products and services) within that brand.
Using “data of the past” works great of you are trying to sell ink to a person who bought a printer, or lens cap to a person who just bought a camera. But get beyond the obvious? Please stop trying to make that happen. It’s not going to happen. It’s like trying to see where your speedboat is going by keeping your eyes glued to the wake. (No joke. Looking backwards to move forward is an inherently stupid approach. It’s okay, we’ve all done it, but it’s time to admit our mistakes and move on. In doing so, you can also leave your competitors in the dust.)
As it stands, you’re probably talking about things like customer intelligence and customer behavior and big data and analytics and [insert meaningless buzzword here]. But you’re probably also analyzing “behaviors” like website clicks and gathering “intelligence” with cookies. We’re here to tell you that clicks and cookies are old school. Old school is good for the base line (your competitors have everything you have now). Time to move on and be predictive and prescriptive. New School is all about looking ahead, predicting, using machines that can learn and drive a business forward.
Do you know where your marketing dollars go? The answer is probably yes, but do you know WHY your money is spent where it is? Every company wants to be more effective in allocating their marketing budget, but people seem to believe that it’s impossible to figure this out.
There’s a famous quote attributed to John Wanamaker, a department store merchant born in the 19th century. He said: “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.”
Clearly this has been a problem for a long time. More recently, Paul Roetzer wrote, “Even the smartest marketers on the planet have absolutely no idea how to allocate their time and money in a manner that eliminates inefficiencies and maximizes return on investment.”
This isn’t entirely true. Or at least, it doesn’t have to be.
Your personality predicts almost every decision that you make, including buying decisions. Yeah, I know you want to disagree, but what kind of car is that in the driveway? Really? So it would make sense that if you understand your customers’ personalities, you can actually PREDICT their purchasing. And meet their ever-increasing expectations before they even know what they want.
Let me explain: we’ve invented a technology that allows you to segment your CRM data into categories based on personality type. This is extremely powerful, for several reasons.
Only 2-4 personality types are profitable to any business. We happen to know which ones, and can show you how to find them within your CRM data.
Not only are personality types the only truly reliable predictor of buying, they are dramatically more effective than the way most companies currently segment their CRM data. (In other words, demographics do not predict desire. But personality does.) Just read what Netflix has to say on the subject.
Traditional Analytics vs. Personality Analytics – so what?
When you look at the differences in buying behavior between a given segment of customers, you’re able to maybe predict that customers in Group A (say 35-45 year olds) are 1-1.5 times more likely to buy Product X than the customers in Group B (teenagers, for example).
On the other hand, if you segment your customers based on personality type, you’ll find that “NF” or “Idealist” types are not just more likely to buy Product X, but they are 30 times more likely to buy that product.
The goal here is to help companies optimize customer acquisition, revenue growth, and retention. Not only can we help you identify the profitable personality types in your existing CRM database, we can also help you find the look-a-like audience by appending our own CRM data.
You know what your customers have purchased in the past. If you can also pinpoint which personality types are 30 times more likely to buy Product X, why wouldn’t you focus your marketing and product recommendations on showing Product X to everyone in your CRM with that personality type who doesn’t yet have that product?
Marketing budget allocation can become a lot more strategic when you apply predictive analytics to your marketing automation. It’s time to move from making semi-educated guesses based on “data of the past” and actually predicting what your customers want using personality analytics. The first companies to leverage this new technology will be the winners in the new world of AI and Big Data. Do you want to make sure your company is around 100 years from now? We hope so. And our goal is to help you do that.
We all know travel and especially hotels is a difficult business. High cost, lacking the technology needed to sustain disruptive forces, travel need a break.
“Hoteliers can build loyalty and trust with guests with the help of CRM technology. This technology can provide a complete view of the customer through the predictive analytics and data-backed insights needed to effectively prioritize customer experience and deliver the personal attention guests have come to expect.”
Hotels are onto something. Brands have few real ‘sources of truth’. One is CRM. When we append rich data to this data set, we discover it can be highly effective at establishing a baseline of rules based on predictive analytics and direction. Once this is established, we can apply machine learning to our outreach, such as apps and websites.
With data mined from a CRM system, hotels can create customized guest profiles to better anticipate preferences such as room category and view, package types, restaurant recommendations, and rates.”
Predicting expectations and why people buy, what they need in-market and out is possible via trait theory and connecting traits to CRM data. Instead of clogging a CRM, we can segment personality and emotional traits that are causal to the buyer, without violating their privacy or experiences.
CRM does not need to be the system of record but can be a sophisticated or simple data platform that predicts outcomes.
If we can predict loyalty and create a total addressable market based on who should be a loyal customer, we no longer require customers to jump the hoops to loyalty. We have a great theory of who already are loyal. CRM can be a modern way to drive greater value. It’s not the simple data set of who bought what anymore.
the study of the relationships between linguistic behavior and psychological processes, including the process of language acquisition.
My work involves this study of linguistics and the psychological process through the gateway of customers and what they buy. By no means do I perform psycholinguistic research and it’s pure form. Instead, I look at real-world human behaviors and convert them into a series of personality traits — all predicted. Theories of customers. Then, connecting traits to sales data, you have some understanding of why people make decisions that impact their pocketbook and the services and products they bring into their lives.
Why do this?
I’m amazed in the decades I have been around that marketers, really don’t understand what I want. I want to be delighted and surprised.
Some of the best examples of delight come from the off-line world. When is the last time the banner ad make you cry? Certainly, the real world can and so can video, compelling written stories, even the old 30-second commercial when given enough time, can work their magic.
Pick up a magazine, a real-world magazine that matters to you. One time I was in Germany and noticed that they had 10 different versions of fishing magazines. I can’t read German that well but I did notice how diverse the subject matter is. The obvious is saltwater vs. streams vs. lakes and of course what you can catch. What was fascinating to me is how marketers used different magazines for diverse products and services. Example: Lake fishing, Audi. Saltwater, BMW and so on. is this random or do they have a great understanding of their audience?
That got me to thinking, can digital media one day reach this and delight me with surprising things that exist in the world that I’ve never heard of.
Do I have to rely on my friends and family to tell me about new things?
Must I come up with a need in my life, a job to be done, and then guess at what product or service is going to fulfill that need?
Can marketers find the efficiencies of what digital has promised and combine it with customer delight, a real-world KPI that Amazon is focused on? Can you bring what works or has worked so well in stores, some stores, and bring that experience online in an economical way.
After 20 years of doing this type of work, why are things still so basic? We’re still talking about topics that I was executing and creating in the late 90s. All of that stuff should be dead and buried and we should have moved on by now.
It’s time for a paradigm shift that includes protecting our privacy, stopping unnecessary collection of data and yet, give people what they want. It can be done and it will be done.
What solves this problem starts with a few basic things:
The business operating system. You must have a mechanism in place that rewards creative, innovative ideas. You can’t just keep rewarding what worked in the past based on what some spreadsheet jockey tells you to do. It’s a flawed system that sets up a recipe for disruption.
You have to understand customers and what delights them. That’s not just a creative or marketing topic, it’s again an operating system that can next what’s inside of your CRM with a predictive CRM, a look like CRM of future size.
Having a theory of customers is critical. It’s integral to the above two items. Theories of customers cannot be solely based on surveys, clicks, and cookies. It can’t be based upon media alone — although that is a great feedback mechanism. It has to be based upon real-world theories of people. Theories have to be tested and they have to have causal connections to revenue.
These ideas are starting to get built into some of the best companies that will in the coming decade, wipe out the incumbents at an ever-faster pace. Organizations need to immediately budget for customer-centric answers yet dial into to significant changes in revenue.
What’s the best way to kill a competitor, grow, and do it fast.
Business OS x Customer Delight x CRM look-alike = growth
While I like this article I would love to see more travel companies focus on brand building and product.
Here are some marketing initiatives in this category:
CRM marketing initiatives with pre-, in- and post-stay messaging aiming to engage the customer, remind of booked services, inform of hotel location, local tours and activities during stay, recommend and upsell services, and make sure guest experience is at its best.
Segmenting customers by traits can yield some ‘not so obvious’ answers about why people buy. Putting people first can yield better product-market fit and less reliance on media. Traits tell us what will delight them.
Upselling and engagement marketing initiatives.
Same answer segmentation by traits drives better up-selling of the right product to the right person.
Marketing automation with drip and event-triggered marketing initiatives.
Something that is needed. But watch the over-reliance on media and what marketing should be doing. Shall I say, product again?
Guest recognition programs.
Loyalty marketing initiatives.
Loyalty and the old satisfaction profit chain model, just updated with A modern approach to CRM can make this quite valuable.
Travel is an exciting vertical. It’s overdue for a rebuild as it’s been 20 years of the same basic methodologies. Companies that do not invest in customer delight and product will find it much harder to mask these problems.
My internet work started in the tourism industry, promoting small businesses in the French Quarter in 1995. That grew into building architecture and selling paid and free media for United Airlines, Hotwire, Orbitz and a number of other cities and companies.
Since those early days, my company has focused on getting to know people, why they travel and why they decide at a deep level. We know why people travel and have a different way of approaching why people pick your DMO to visit. We find insights that are different, beyond age, race, and simple demographics. We focus on the linguistics of personality through our technology and 20+ years of understanding the details of getting heads in beds.
Theories are nice but having concrete material, focused on tax revenue growth is better.
We know your team needs specific help and we never lose sight of that. This is not just how we make our money: it is truly our passion.
WHY WE ARE DIFFERENT THAN ANYONE ELSE
My background is similar to yours. I love tourism and also love figuring out why people buy, but I never liked or believed in cookies or click data. It’s not bad data but it often misleads us in the tourism world. Tourism is very much an online and offline experience. I sold a company to Google some years ago and at their suggestion, I got into the predictive CRM business. CRM is a source of truth that helps define why people buy.
If you have a really big CRM, you can figure out why large groups make decisions. Through studying the psycholinguistics of human activities, such as travel, jogging, scuba diving, etc, we form theories about why people do what they do. I have a degree in abstract mathematics and have been practicing computational linguistics for 25 years. For me, content is not just a story but deep patterns of how people think.
The idea is to find a source of truth in your studies, your city, region, visitors and your CRM. While avoiding strict data of the past methodologies, I can infer why people come to your DMO. Inferring from past sales data is fine in many situations, but it becomes powerful if you combine it with predictive data. You probably recognize some of this thinking from Clayton Christensen. He is my main influence, along with David Oreck on how to use data of the past with theories of future behavior.
I acquired two sets of data over the years. One is a CRM which represents most of the United States buying public. It’s about 233 million people and I’ve combined it with psycholinguistic calculations on why they buy. That’s the real nice theory, but it becomes powerful when you connect to research or CRM data. This allows brands to understand audiences in a whole new way, write content that is gripping, that describes your DMO well to the perfect visitor and it helps people make much better decisions about where to go and what to do.
I also have business data on 80 million people and the types of businesses they work for. This helps define the market ecosystem.
By combining all of this together along with information from your DMO, you can remove a lot of executive bias, speed up consumer research, and get content out that is profound and meaningful.
I would call it an ideation process backed by powerful technology. The idea is to limit the bias of people as much as possible and find sources of truth that are predictive in nature.
It works very well.
There’s two postulates that I’m working on:
Only 2 to 4 personality types are profitable for any given DMO. Understanding who best fits your DMO drives higher ratings, better content and more influencers. Ultimately, it means more tax revenue.
The profit differential between best customer type personality and least is at least 10x. Bringing the wrong visitor leads to lower ratings. They don’t return or buy as much as the best customer. So why “average” your efforts when we can find the ideal customer types?
When you look at conversion rates online, and how dismal they can be, you see why marketers tend to swing too wide. Conversion suffers tremendously. Your DMO is an equalizer to the machine-driven thinking that can crush a DMO.
Store conversions above 30% makes sense because the salesperson can be adaptive to the buyer and the very nature of stores is much more dimensional and visual, which aids in basket size and conversion rate.
If you can bring store conversion rates to the online experience, you have an amazing DMO. I’ve been able to increase conversion rates by focusing on who matters most and building look-alike audiences not based on clicks and cookies, but real customer desire.
Bringing a more human way to market to online drives tax revenue.
Imagine building content that speaks to the ideal customer like a National Geographic Traveler magazine with the power of data and machine learning technology. It’s is what drives focus, prioritization and tax revenue.
THE DETAILS — HOW WE CAN HELP YOU
Find what matters, empower a team, be empathetic, and focus on growth. We assist creating governance and help you define priorities while motivating and emphatically bringing a team together. We help you create process in a chaotic world. Find what matters, open eyes, and grow. Whether it is helping create governance or writing process, our passion is finding you the best visitors.
Scorecard and operationalization drives our decision-making process. We can successfully put in place a way to measure content to tax revenue. By looking at analytics, combined with tax revenue, search data, you can prioritize your next moves.
Dashboards: We help create dashboards that present meaningful information. We live in a world where too much data exists and many struggle to boil it down.
SEO and SEM: We invented ways to create traffic and can get you to 50%+ traffic from free search. We know what search engines expect and what you should expect from search engines.
Gap analysis: Find what is missing on your site using big data combined with site and app traffic. Google expects certain content in order to rank you appropriately. Gain traffic and tax revenue with relevant tactics.
Link analysis plan: This plan shows what sites are not linking to you and who should. We often see links come from easy to get places while the big sites don’t show up. That creates a gap. We have a way to reach out to journalists to promote linking and content creation, which drives traffic and tax revenue.
Content x links = great SEO and tax revenue growth. By prioritizing certain content that is relevant to your DMO, you gain certainty about what matters most.
Competitor analysis dashboard and supporting data: We don’t focus chasing what others do but it can help.
Built-out detailed studies of travelers by segment based on ‘why they buy”. Find out where they go and what they are interested in when they are in market and out of market. We can create custom studies and help define content, even down to what verbs certain segments read best. The experiential traveler is a hot topic and we understand who they are and how your content writers can best approach for your market.
We help you do real work and prioritize what matters
Authentic, real, and personal
In a day and age of ‘Machine Darwinism’, understanding who is real and who can drive value for your your DMO is difficult. Machine Darwinism is when algorithms build content based on data. Ratings, placements, and facts become traffic drivers. The ‘why’ is lost in fads. Machines and platforms can’t solve the problem. Machines might drive traffic but they often fail to persuade people. Your content writers need help to overcome this problem.
While data can’t persuade people and solve ‘why’, you need data to drive focus on who is interested and what it takes to convert them.
We have business data including the econometrics of the tourist economy of your city
We have people data, 233 million people in all and understand why they travel and what they desire about your DMO
Data is the foundation that allows your team to focus on what matters — driving tax revenue
STRATEGY
It does not take long, but getting alignment on your strategy is critical.
Understanding your customer
We have developed a scorecard methodology that looks at multiple ways to see a person and the businesses that serve your economy. Our methods do not focus on any one metric, our methods prioritize what to work on first without creating complexity. It’s important to blend many different things such as time on site, click through rate, and bounce rate to name a few.
By prioritizing the most important visitors you can better understand in and out of market priorities for each segment and build content according to their expectations.
By understanding the psycholinguistics of people, you can better build content that interests them.
Measure only what matters and what drives real value. Example: who is your best customer and do you have itineraries designed just for them?
Having a strategy that prioritizes, tests, ramps, and expands what works is important to your DMO’s future.
Building plans that work
We help you define marketplace trends using past, present, and future data sets. Prediction data helps create theories of the future. It is vital to include that data.
By using sources of truth, we can find sound evidence on where to develop plans and guidelines going forward. As people change, their demands change and your members and businesses in your market must react faster than ever.
You supply data to your stakeholders and members that can influence what is capitalized and what is invested in your market.
MORE DETAILS
Business Data
By understanding who is conducting business in your DMO, you have a sense of what exists and how well it serves the visitor ecosystem.
Revenue per person by Business Type: informs you who is profitable, who is doing well, and who is not. Who needs your help? This prioritizes which businesses can best serve what types of tourist.
Economic zones: where is the next area to develop to incentivize?
Some examples of business data that helps define the conditions in your DMO: revenue per SIC and revenue per website.
START WITH YOUR WEBSITE
What should the architecture of my website look like? Does that affect crawl and ranking? These are just two of many questions that are critical in building a website that drives traffic and visitors.
By defining what people are looking for, not looking for, and then building the site in such a way that search engine crawlings rank well, you solve one of the critical pieces in curiosity to tax revenue.
We help build and transition websites. One recent success is New Orleans.com; for over 15 years New Orleans has had multiple websites. We helped craft the agreement to have a single website entrance from multiple sites into one without negatively affecting visitor volumes and tax revenue.
We help how teams work together and how you can help prioritize and scorecard what should be the priorities for driving tax revenue.
Search research
We can gather the search terms that drive visitors to websites and help you define what are the best search terms and content to build.
What is the gap analysis?
DMOs are the great equalizers. In an age of machines ranking websites based on user ratings and social currency, a DMO can help redefine what a city and region is about fairly and responsibly. You can correct what often can be turned into a facade economy.
RESEARCH — BRING POWER TO THE TABLE, FAST
Help determine the impact of modern technology on the supply and buy side of your tourism economy.
How does Airbnb affect tourism outside of well-known areas? How does Uber contribute to driving people into different regions of your market and its impacting spend?
SEO
Determine how your website is performing, where to best get traffic, and how to yield the most from free search. If your site is not getting 50 to 60% of its traffic from search engines you might have a problem.
Write titles and descriptions as well as architecture to improve search ranking.
Determine technical issues that could be affecting crawling and indexing.
Help educate your writers on how to best combine SEO writing styles with reasons for visiting your DMO.
Backlinks and linking: how to help journalists who are influencers find material. How to get quality links that drive traffic and search ranking.
We have a unique way to measure and prioritize where you should seek backlinks. It is one of a kind and helps create a priority that can be tied to tax revenue.
Social: help determine real social influencers. Reach out to legitimate content creators that can help craft real content. How to budget for this, how to determine what value to expect.
Example: we recently worked on a website that gets less than 2% traffic from social. The particular location has great social currency, but the real value comes from traditional journalists. One article in the New York Times is worth millions of social postings. How do you determine who is authentic, who is going to drive traffic and value at a reasonable cost?
SEM
We help you determine what works and if you should buy paid search media. Often, a long tail strategy can work, but who is setting up 10,000+ phrases and how much should you pay?
We have a long history of buying media for travel sites: United Airlines, Orbitz, Hotwire to name a few. What you should buy and how you should buy it is important part of a paid media strategy.
Building content with you or for you
Because we know people at a deep level and why they want to travel, we can help you build actual content whether it be itineraries, articles, or organize things to do according to visitor types.
BIG DATA
We can perform cluster analysis of why people travel. Using linguistics software, we can ethically discover why people come to your market and what are their needs, reasons to decide, and why.
The diversity of people makes content a challenge. By understanding people at a deep level, you can segment, cluster, and better convert thought more effective creative.
We have many variables that make up your DMO’s economy. Data can help you define who to help, who should be involved.
Store density by employee size and can be configured for heat mapping revenue/employee
Density mapping customer intent by subject matter is a great way to find what people want and helps focus content and media execution.
Here is a list of variables we measure
Examples of NASICS tourist business descriptions
Example of Psycholinguistic research that helps define how to write and what to write. By connecting this data to CRM data we can help Define who is visiting and who is the target segments. That helps Define a Content schedule as well as the tonality of how to reach them best. The blow example is people that Garden in Iowa.
CONCLUSION
We are here to help DMOs grow. We understand people, specifically travelers, at a deep level that sets the foundation for content, media, prioritization and design.
We are here to help you, not take over. We are an empathetic asset to help you get ahead and grow. By empowering teams with understandable information that can be put to use right away, we remove the unknowns.
It makes the process of utilizing JTBD theory faster, easier and cheaper to execute. The Clayton Christensen theory is critical to figuring out why people buy. Dr. Christensen has been very important to my career growth and ability to “compete against luck”. By identifying your best customers’ desires and reasons for ‘hiring’ your company, you can find more, speak to them as you know them. Having software allows you to speed to market faster, have an “always on” approach two jobs to be done without invasive techniques.
By combining predictive theories of people with core business data, you can see over the horizon. Reprioritize your distribution of profits based on the ability to delight customers. Finding out what motivates your customers, and unlock the customer journey, you are no longer at the whim of media.
If you’re trying to understand your customers through media and those KPI’s, you’re going to be always disappointed in the results. Media produces minimal KPI’s while maximizing their profitability, not yours. One way to think of it.
You have to reduce your audience size using prediction.
In a recent exercise, I removed 98.5% of the audience to get to an exact look-a-like audience.
This is designed to help you see your CRM in a whole new way, a psycholinguistic way. I help you figure out why people buy long before they know what they want (predictive analytics). I look deep into what delights people (customer delight as a KPI) about your company. Having a deep understanding of people is a lot like knowing a friend. It significantly impacts conversion rates and retention.
By the 1960s consumer-oriented marketing begins to take shape. I was privileged to meet one of the first “mad women,” a real Madison Avenue Ad executive. She told me her favorite story was salvaging the message and marketing of the 747. The elements of early consumer marketing were taking hold.
As early as 2006, consumer-driven answers started to take shape with the advent of more advanced CMS and precision targeting. A big factor was media was still cheap, and the economy was great.
Today the consumer is in the driver seat. Social, ratings And a host of other democratized answers give us a flood of data about products and services. The downside is there’s far too much data, and it takes a great effort to learn the actual story. For example how many 4.0 or above restaurants have you been to lately but just don’t fit who you are?
It’s great that the customers in control and people are thinking customer centricity and personalization. As media costs keep rising, We need to bring CRM and look-alike CRM to the table.
While media companies need to make profits, overreaching 95% is not tolerable for many smaller businesses. Companies need to precisely create look-alike audiences based on CRM and theories of why people buy. It’s Jobs to be Done Theory, but the execution must be through media channels and creative for profits to be realized.
If you’re not creating a look-alike CRM, you’re in a fools game of overreaching people that will never buy. Never. If your conversion rate is not acceptable, you’re overreaching. If your cost per acquisition is not acceptable, you’re buying far too much media.
This is an in-between time. A lot of things have been done and done well, but it’s time to focus on who the customer is and their Job to be Done. It can be discovered by understanding their traits, not demographics. It can be realized through one-to-one media not based on the KPI’s of the past but based on theories of people, their traits and personalities.
Once you have your look-a-like total addressable market or mirror CRM, what comes next?
You have many options.
Once you have your lexical based trait analysis of customers how can this be used to reach audiences? By having an entire look-a-like CRM inside of your CMS/CRM, you can generate experiences as if you know the customer already. Matching by batch or in real time is possible.
The number one output of doing this type of work is to improve conversion. Every website and every app has volumes of people that don’t convert yet look exactly like great customers. They sign up for newsletters revisit multiple pages, they downloaded your app and shop, even putting things into a basket yet they just drop off and disappear at rates beyond 90%. It seems so debilitating. It makes you wonder why they even came to the website in the first place. They searched for the product you have in stock or even your brand, yet digital conversion, compared to stores is small.
By giving the desired visitors the experiences as if they’re a Mileage Plus Gold status member already, you’re presenting the best customers with options and product they expect. That does not mean everyone. Some people want Tahiti, some want London. Don’t mix it up. And it doesn’t have to be weird and awkward. But what you suggest, can be far better than it is now by using traits and a guide. eBay is starting to do it via emails. Netflix does it at the script level. By combining a look-a-like CRM, with app and CMS integration, you can significantly improve conversion.
One way to think about itIs going back a few years to how we did retargeting in display advertising. It’s a cookie -based system that just keeps reminding people until they give up. It performs great when done right. It’s a bit of a stretch of an analogy but the idea is similar. If you give an amazing experience and reminding people, they’re going to convert far better.
Another way to think about this is the off-line retail experience. I’m talking about a great store in Mayfair, London. Some of those stores are so specific and they know their audience well before they come in. Once you are in, the store, service becomes adaptable, focusing in on getting you what you need. Stores like this convert incredibly well, Upwards of 50% of the traffic coming in, find something to buy. Great stores convert incredibly well. What Amazon is getting ready to do with their retail physical expansion will bring the same type of thinking and conversion.
How the product is described and what it says can have variations based on who you are. So for anyone product, conversion can increased by dynamically triggering different text, images, etc from the CMS based on a connection to the look-a-like CRM. The current way of thinking is to do this based on page visits and clicks and even importing data from Google to better understand people. It works but it is weak. It’s no comparison to that Mayfair store.
The other clear output is marketing.
By finding ‘segment densities’ of people, you can change how digital marketing and its results work. You will notice there are many places and people that don’t fit what you do and don’t see your product as a solution to their job to be done. Our research indicates traits have a geographic component that is connected to traits. How places formed, the reasons they exist are deep rooted. By finding them, you can connect traits to people to profits.
Even things like life insurance have different pockets of density throughout the country. I have seen great insurance brands with a handful of locations above 10% market share while the rest languist at less than 1% market share. By identifying segments and where they might live you can use digital marketing is a very different way. You can ‘heavy up’ in high density areas and avoid others. CPC might be higher but in the end, profits matter more.
Another output is direct-mail. If left up to the direct-mail house you might over market. By handing them a list based on traits, even at a higher cost point, you can convert far better then paid search.
There are other 1:1 opportunities through display, TV and a host of other technologies that allow us to market to individuals or to households. A few new direct response oriented brands have been built on this foundation. Organizations worth billions are more likely to focus than to ‘spray and pray’.
By starting off with a precise view of customer segments, defined by traits and slowly expanding audience segments in unique ways, organizations can disrupt competitors with innovation that is ready to go.
How are you doing you’re 1:1 marketing these days? I’m curious to see what other people are doing.
