Author: christopherskinner4136

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By Arranging Our Multiple Personalities, You Could Win A Million Dollar Date

Alphabetically, size, price, type, similarity, and even random are just some of the ways companies with large distribution centers arrange their warehouses in order to optimize time between order creation and fulfillment. Similar to how UPS revolutionized the logistics of home delivery with their “no left turn” strategy; is there an optimal way to arrange products within a warehouse to reduce the time-to-fulfillment thereby lowering overhead and increasing customer satisfaction?

There just may be, and the arrangement is by personality!

Our findings show that people buy primarily based on desire and justify the details in order to satisfy inherent feelings. Is it logic? Are we just being human? The creative types have been saying this motivation has existed for years but it has been difficult to verify. What about the camera you just bought? Yes, you are likely to add a lens cap and case to your purchase which intuitively means fulfillment centers should be arranged in such fashion. But is it possible that something that appears irrational on the surface is actually the most optimal in practice?

If products were located based on personality in fulfillment centers, much shorter distances may be traveled by warehouse staff. Even in the wishful days when machines are extracting all product, a ton of energy and time can be cut if we physically locate products based on desire, personality, and traits. In addition to cutting time, accuracy of orders will increase dramatically.

It’s time for warehousing, distribution and marketing (recommendation, merchandising, etc.) to get on the same page. Time to locate the wine next to glasses, strawberries next to chocolate and make everyone’s lives more efficient and profitable. On the surface our logic appears random but the data backs it up. Products that seem very distant should be collocated in the warehouses, on the shelves, and in marketing plans. Just like dating, timing and personality is everything.

Let’s take a look at how two well-known e-commerce sites with millions of orders arrange and operate their fulfillment center. Their actual names will be genericized for discretionary reasons. We’ll review their initial intake/stocking methodologies and fulfillment processes in order to gage whether the hypothesis that stocking initial intake of products by their correlation to Myers–Briggs Type personality can reduce time of fulfillment. As a reminder; Myers–Briggs Type Indicator (MBTI) is designed to indicate psychological preferences in personality and decision making by which humans experience the world – sensation, intuition, feeling, and thinking – and that one of these four functions is dominant for a person most of the time. The MBTI was constructed for normal populations and emphasizes the value of naturally occurring differences. “The underlying assumption of the MBTI is that we all have specific preferences in the way we construe our experiences, and these preferences underlie our interests, needs, values, and motivation.[1].

Site A Operations:

Intake and Initial Stocking Methodology: Random. As products arrive they are placed anywhere in the warehouse that has space and the location is scanned into the system.

Fulfillment Methodology: Prior to an order being filled an algorithm based on the quickest time to fulfillment generates the optimal path for individuals to take within the warehouse.

Figure A provides an elementary optical overview of Site A’s warehouse operations. In this example, items are stocked randomly. When an order came in for a two CD’s, a baseball bundle and a pair of shoes, based on where the items were randomly place upon intake, an algorithm generated the optimal path to take around the warehouse to collect the items to satisfy the order.

The benefits to Site A’s operations are that minimal time is spent during the intake and stocking process because any product can go anywhere, as long as the products location is identified while stocking. The algorithm that generates the optimal path for fulfillment is the key component to the success of this process. The questions are; does the time that Site A saves during the disregard for intake and sorting supersede the time spent on fulfillment even if the fulfillment path is optimized? Should consumers’ action and personality be a factor in these logistics?

Site B Operations:

Intake and Initial Stocking Methodology: Product based. As products arrive they are placed in designated areas in the warehouse; traditionally by Global Product Classification (GPC) or United Nations Standard Products and Services Code (UNSPSC) which classify products by grouping them into categories based on their essential properties as well as their relationships to other products.

Fulfillment Methodology: Prior to an order being filled an algorithm based on the quickest time to fulfillment generates the optimal path for individuals to take within the warehouse.

Figure B provides a simple visual overview of Site B’s warehouse operations. In this example, items are stocked by products and product similarity (i.e. CD’s with electronics, shoes with clothing, etc.). When the same order came in as in Site A’s example (two CD’s, a baseball bundle and a pair of shoes) based on where the items were place upon intake, an algorithm generated the optimal path to take around the warehouse to collect the items to satisfy the order.

The benefits to Site B’s operations is that the layout of the warehouse is logical and products are easier to find if an algorithm is not available. If an algorithm has been developed to generate the optimal path for fulfillment it is still a key component to the success of this process but not as dependent as Site A. Site B has some flexibility in the algorithms accuracy due to the logical layout of the warehouse. The questions are: did the upfront sorting and stocking by product classification save anytime when making fulfillments? And as with Site A, should consumers’ action and personality be a factor in these logistics?

The simple answer is yes and yes! We have been stocking warehouses relatively the same for the past 50 + years, it may be time to arrange by our multiple personalities.

If we understand how each of the 16 Myers–Briggs Type Indicator (MBTI) are attracted and related to each product we may be able to arrange a warehouse based on personality and likelihood to purchase as illustrated in Figure C. For instance, the ISTJ personalities are defined as responsible executors. Individuals with this type of personality are generally attracted to logical and conservative products such a simple black or blue suit, tasteful furniture, and standard cleaning supplies. So can products be grouped into personality likelihood of purchase? The answer is yes! MakeBuzz uses proprietary computational linguistics software to translate the hundreds of data points they’ve aggregated on a persons’ interests, demographics and activities into a set of traits that make up Myers-Briggs types. Their database contains the personality profiles of over 219 million people, which means they can generally match ~50 % of any given CRM filled with products and consumers actions.

So what if arranging products by personality in a warehouse and could save 1, 5, or even 10 seconds off the average time of fulfillment. What could that do to operating costs? Table A illustrates just that.

If a well know e-commerce site accepts on average 35 orders every second based on an 8 hour day and arranging their warehouse by personality reduces time to fulfillment by only 1 second, the site can save almost $80,000 per day or over $28 million in efficiencies per year. If the fulfillment time can be reduced by a mere 10 seconds the annual efficiency savings could surpass $86 million.

Without leveraging consumers’ personality traits and how they relate to potential product purchases we may missing out on an opportunity to optimize operations in large distribution facilities. If we are able to combine current organizations CRM’s with personality traits we begin to paint a more robust picture of consumers which ultimately proved better experiences and increased revenue.

This hypothesis can easily be integrated into an organizations current operations and tested prior to any warehouse reorganization. Historical data can be used to measure actual results and actual savings via a virtual warehouse configure by personality type. So, to ensure success in the future, perhaps it is time to arrange us all by our multiple personalities in order to be placed on a million dollar date.

Co-Authors:

Tom Stanek: Versatile, dynamic leader and team builder offering record sales with top level consumer and client support.

Christopher Skinner: Personality software Inventor – connecting personalization to personality.

[1] Myers, Isabel Briggs with Peter B. Myers (1995) [1980]. Gifts Differing: Understanding Personality Type. Mountain View, CA: Davies-Black Publishing. ISBN 0-89106-074-X.

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Creating Delight in Online Retail

It’s not just that online commerce is taking sales away from retailers. Well, it is, but it’s far more than a one to one ratio. The problem is not that Bob Smith bought his comforter set from Amazon and therefore Target lost out on the sale of a comforter. What’s really happening is that every online purchase is actually one less human being that walks inside your store. Why does retail not innovate around this problem?

Think about this: when’s the last time you found something really new and amazing while shopping online? Have you ever gone to Amazon to order, say, a case of this delicious Trident gum (Peach Mango) because you can’t seem to find it in stores anymore, only to discover an EVEN BETTER flavor of gum? No. You search for the gum, because you know you already like it, and at best you’re going to see that other people who searched for this item also looked at different flavors of gum.

Online shopping is too often about direct response. You search for something because you already know you want it, and so you go online and type it into Amazon or Google.

But how did you know you wanted it in the first place? You had to discover it first.

I definitely didn’t discover the (sadly) soon-to-be-discontinued Peach Mango flavor of Trident because I was doing literally anything on the internet. Shopping or otherwise.

No. I discovered it because I was in the checkout line at the grocery store, and it caught my eye. I bought a pack, tried a piece, and realize I’d just discovered my absolute favorite new flavor of gum. (This rarely happens — most of the time trying a new flavor of gum leads to reactions ranging from slight disappointment to mild disgust to WTF was I thinking when I put a piece of ham flavored bubble gum in my mouth.)

Impulse purchases. Serendipity. Discovery. Surprise. These things do not happen often enough in online stores. They happen in real life.

This seems obvious to me now that it’s been pointed out, but how often do you search for something you don’t already know? Never. Right?

Search is a very specific tool, that has more limited application than I used to think. Most of the time I find myself using Google as a handheld dictionary (define: obsequious) or as an argument-settling oracle (Wikipedia says lobsters DO come in both red and blue).

You can’t search for something if you don’t know it exists. So how does discovery happen in a post-Amazon Prime world?

I invented a technology for the purpose of bringing that offline experience of discovery and surprise to online retailers. And likewise, bring the online to the store. Disruptive technology can’t replace the kind service staff nor can it replace the charm of a well done shop in Mayfair, Union Square or the niche beauty of Royal Street. Hopefully we find a balance and realize, one day, it’s not us vs them. Both can and should support each other. Both must understand the customer far beyond clicks, cookies and coupons.

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How happiness can be understood with large scale computational psychometrics

There are several major technical areas to solve in order to quantify customer delight.  Customer delight is a well-documented, but hard to achieve KPI. It is a form of “measured happiness”. Jeff Bezos understands how important it is and has 5 teams working on it at Amazon. It’s that important.  

Most organizations prioritize deep understand of “data of the past”, a term Clayton Christensen, the well-known Harvard professor, uses when describing the shortcomings and ultimate demise of market leading organizations. By focusing on data of the past, even if you are applying predictive analytics to that data, can lead to shortcomings and misleading results. Many organizations predict the obvious because it is safe to do and creates the least amount of risk to the culture of the organization. Just ask Kmart, Sears and GoPro to start. Reinventing oneself is not new and it should not be so hard.

While Clayton is fascinated why great organizations fail, we would like to see that issue avoided. If technology can help, the better we all would be.

Data at scale is a start. Having massive data at scale on people activities means one has the building blocks of a better way. When you understand what people do in their lives and work helps form the basis of understanding why they make certain purchasing decisions.  

Having a job to be done is fine, understanding why the job is to be done is much better. People are different and combining Big Data with predictive characteristics of people based on that data drives real results back to CRMs.

Many companies can quantify human activities, demographics, income and wealth data. Many sources of data can tell us what types of occupations and cars we drive. What this lacks is what does it mean to be a scuba diver, a plumber, drive a certain type of car and on and on. By converting human activity and demographic data into predictive psychometric data, one approaches a much better understanding of who our customers are and why they buy. It leads to quantifying what delights people. When Clayton talks about “jobs to be done”, the lack of a psychometric context of the person limits the choice that person will make. By understanding people psychometrics at scale, you can see CRM patterns that are otherwise invisible.

We have discovered that what drives sales, psychometrically, can be described by a handful of variables closely associated with a person’s personality and traits. Those variables are much greater indicators of what will be purchased in the future than past sales data, cookie data and the like. Just because you went to Paris does not predict you will keep going. Today, companies like Amazon do very well “predicting” ink sales if we buy a printer. They recommend we buy lens caps if we buy a camera, cases if we buy a hard drive. While these are good reminders, they are not delightful. Lacking delight opens up the risk of price shopping and loss of brand equity of the organization, something Jeff Bezos understands well. No one can win a price war in the long run.  

The words people use can be converted into a rich understanding of their beliefs, desires, relationships and personalities. By understanding cognitive patterns and connecting to CRM data, we find the psychometrics of the CRM. Doing so creates certainty which drives speed and alignment with the organization. If you ever fretted over an analytics program, you understand how so many choices often do not lead to a clear path.

Once we understand why people buy and are delighted, we have a clear path to creating customer delight and remove complexity and uncertainty within the organization. Customer delight is broken down into 3 key elements:

  1. Create customer loyalty. Instead of rebuying your customers through paid media, how can we get people back easier?
  2. More profits. Easy to say, hard to execute. While many businesses are offering discounts right away, having customer delight slows down the coupon bus. Apple does not have coupons, you don’t need them either.  
  3. Reviews. A customer who gets it, says nice things, online and to friends. They own it, flaunt it and you win.  

According to a Bain & Company report on Net promotor score and profits, only 9% of organizations surveyed could sustainable profits and growth for 10 years. By understanding the psychometrics of people within our CRM, we eliminate complexity, the enemy of certainly.

Our research has found that only 2 to 4 personality types are profitable for any given SKU or product line found in an entire CRM. When we look at market share of most companies and we examine the details of the Bain & Company search on sustainable profits, we see a reason why organizations are limited. They spend most of their funds focused on people they cannot delight. It creates anxiety and frustration with the organization, expending resources with no outcome. We found that a 10 to 1 difference exist between the most profitable personality vs the least. Organizations that understand why we have a job to be done are most likely to scale and outperform competitors.  

Organizations that focus with the end in mind and prioritize what is important most, can create customer delight. A 5% increase in customer retention alone can yield 25% to 100% increase in profits if they have the predictive data appended to their CRM. Companies that go beyond the CRM and create look-a-like models can locate audiences that while harder to reach, prove to be a better path to sustainable profits and long term happiness, both inside and outside the organization.

We know this is a complex topic and we left out a lot of secret sauce. Contact us if you want to solve real problems, we are delighted to share how and help you reach that better place. To learn more and see how we can help you, please contact us.  We promise a call is worth the effort.

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Innovation begins with a great idea?

You have an idea. And what happens next goes something like this:

The idea is fleshed out. Then it’s funded. Then it’s enhanced, tinkered with, focus-grouped, and marketed. Then you tinker with it some more, and, finally, you bring it to market. Sound familiar?

If you’re lucky, potential customers will love your idea as much as you do. If you’re really lucky, they’ll not only pay you for it, but they’ll also tell their friends about your great idea. And if you’re really, REALLY lucky, your idea will catch on. It’ll go viral, as they say, and embed itself into the public mind.

At this point, you’ve made it. Your work is done. Right?

Not so much.

Because when you make it, something happens. Your idea does so well, your customers love you so much, they start chomping at the bit for a new idea! A better idea! They expect you to replicate the same stroke of genius that made them love you in the first place. They’ve come to expect this from you.

Here’s the problem: you don’t have a new idea. But that’s okay, you tell yourself. You’re going to market the hell out of this one! Add a bell or whistle. Tweak the formula, change the color, offer a discount, and come up with a snazzy new logo and brand identity. That’ll do it! Right?

No. It won’t. And it doesn’t.

You end up spending time and money on ideas that fall flat. You don’t have revenue to show for all the resources you’ve put in. No matter how hard you try, how many bells and whistles and new features you add, your company has hit a plateau.

No more growth. Now WTF do you do?

This is where MakeBuzz comes in. I’ve been helping build hyper-growth organizations using a set of principles based on the idea of disruptive technology. Disruption has become a buzzword, but in reality, there’s a philosophy behind it. The process I use involves systematic innovation, agile management, and prioritization principles.

The results? Technology-driven solutions that focus on a customer’s ACTUAL needs and wants. In other words, I make a living helping companies restructure by showing them the path to responsible, sustainable shakeups. No bells and whistles required. (Or, even worse, logo redesign.)

Here’s the trick: you need to find a balance between old-world principles and the ever-changing opportunities of 21st century commerce. Every business has many moving parts, but increasingly there are three major parts that fall apart faster than ever:

  1. Lack of understanding the customer at a core level.
  2. Incomplete, haphazard, or weak products.
  3. Inability to understand how to reach customers.

There’s enough to say about the first two issues to fill a book (maybe later). But item number three is quickly improving. And this is giving SOME organizations hope. Hope of survival, that is. The world is changing so quickly, most companies can’t keep up.

Here’s the history. From 1999 – 2012, digital media could be arbitraged at scale, and traditional marketing could still create real brand equity to support the emerging, direct response-focused world of digital media. Personally, I used to take advantage of search. First, SEO. Then SEM. I would “buy the dictionary.” Low bid it all, seek out the performers, and scale. Call it the Darwinian version of direct response marketing.

I became pretty good at data management platform (DMP) technology, which allows a business to streamline digital marketing. But then, something happened. Technology has evolved, as it tends to do, but this is not necessarily good news for brands.

Here’s why:  

Less than 10% of all available inventory (of search terms for SEM, for example) is not profitable to brands. As online publishers approach the cost of traditional print publishing outlets, something changed. Building a business is not easy, and now that a funnel that used to be affordable isn’t, you see the problem.

What happens next I call “saving your way into bankruptcy.” Companies move to trim the fat, which almost always leads to a downward spiral. You have bad ideas (which, really, you don’t even need) multiplied by bad top of funnel. There’s no real demand creation, only perceived. It’s like vanity metrics (engagement, likes, friends, followers) for CRM building. Yeah, you got 50 new contacts in your database, but they cost you $50 each and you don’t even know if they’re high-value customers. This is not a strategy that leads to profitability and growth, or even survival (if we’re going to be honest).

Marketing should only reach a named, addressable audience. It should only use media that is strategically crafted to create real business outcomes. (Hint: redesigning your logo and “modernizing” your brand identity does not lead to sales. You want sales, right? If not, stop reading.)

It’s no secret that most companies operate below capacity. Or maybe it is a secret, because so many of them do. But the truth is they shouldn’t. And they don’t have to. There is a better way.

This is the reason I jumped ship on digital media as we know it. And I think you should, too. Here’s what I suggest.

Flip the model: why bother with media and advertising, incrementally building your CRM, when you instead you can start with a named, addressable audience. Instead of incrementally building your CRM database, when you can have the CRM for the entire United States and then filter down to find your best customers from there?

Because it’s impossible, you say? Actually, it’s not. That’s what I help companies do.

What happens is you’re able to create a tangible “future CRM” filled with clones of your very best customers (look-a-likes). Then you can invest your marketing dollars on media that speaks directly to them. Only the people who truly want and need your product. Thus, you’re building your business on reliable, predictable growth that can be aligned to the financial management of the company.

Your chief revenue officer is going to love it. In fact, you may become the next CRO.

Instead of filling your CRM “bucket” one raindrop at a time through expensive and unpredictable marketing, why not start with a bucket filled to the brim? Then you can filter out the contacts that don’t belong, and scale your company from there.

I predict that by doing this, your company will grow to its optimal size and operating capacity MUCH more quickly than it would otherwise. Not only will your company survive in the age of Amazon Prime, but you’ll leave competitors in the dust.

This is the future of CRM. It’s a cutting-edge way of looking at marketing. And, more importantly, it works. In the past, this approach wasn’t possible, but the dramatically increased capacity of data storage, computing power, and connection speeds have changed everything.

People often forget, but these concepts are critical in a true big data environment. And the good news is that it’s now possible for every brand to have their own “customer clone” look-a-like CRM based on real world data. This enables incredibly fast growth to a company’s optimal market size. You can do infinitely more than in the past. Predictably, and at scale. The challenge is to put the people and processes in place.

Are you ready to move faster? Does your business allow for experimentation? Taking chances? If so, the time to flip the old model is here.  To everyone else, best of luck. You’ll figure it out eventually. Hopefully before it’s too late.

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Think of Your Business Like a Lawn

At Google’s ThinkFinance conference in Mountain View, CA the title of the keynote presentation was Digital Measurement is Broken, Let’s Fix It. 

During the hour, I shared the concepts and case studies that have helped companies form a different framework for media planning and measurement – one that I hope will correct many of the limitations of current methods, to become the new standard. This goal of this new framework is to help business seek out maximum profit volume, on a market-by market basis. Profit by volume, as MakeBuzz describes it, is the ultimate measure of efficiency – and the ultimate measure of growth. I suggest that our marketing objectives have been disconnected from this fundamental business goal for too long.

An update: Since our time with Google, we have moved on to 1 to 1 marketing, via named addressable marketing. This removes 90%+ of the post cookie audience and over 50% of the non-human media. Thus, performance is truly impacted.

Think of Your Business Like a Lawn. And the blades of grass are your profits. When you’re watering and fertilizing, you’re making the grass grow- that’s your branding. When you’re mowing- that’s your Direct Response.

Your lawn needs both these efforts to grow it’s greenest and it’s best. By the same token, a healthy marketing strategy is made up of Branding and Direct Response efforts in perfect balance.

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Avoid “averaging” the customer journey

[Writers note: In late 2014, we wrote this article. We had not invented our CRM technology, but we knew that there had to be something better than simple demographic data to segment customers.]

The customer journey is complex. It has always been that way. The human mind is not something you drop into a Skinner Box. There has not been a linear path to anything since the days of the butcher, baker and candlestick maker. Follow that?

When attempting to sell something, build brand, profitably, you have far too many things to contend with. Where do you start?

One place I like to start is with finding customer density and potential customer density. Ideally, starting in neighborhoods and then down to the individual. In the chart attached to this post, you see an example of great differences in eCommerce sales density vs store sales density. By avoiding averaging of customers, by area, by segment by product sold, you avoid average results.

My 4 items to look at:

  1. Building audience, one area and person at a time. Start by finding audiences and determine where audiences are not. That is the most basic of segmenting audiences. The marketing ecosystem often oversells media. Just look at your CTR and conversion rate. Why have these numbers been accepted? I think it is this way, in part, because we average results. Add in Viewable impression data and up to 70% non-human traffic and something is wrong with how current technology chooses audience. Audience data, both cookie and pre-cookie is a critical first step. Avoiding averaged audiences is a great step. (2018 note: we are still firm believers in not averaging customers, but now we’re got a much better way to bucket them. Also, take a look at metrics beyond Google Analytics. Customers are more than just click-throughs. Our CRM has human activities that tell us why people buy.)
  2. Focus media in areas where the FULL customer journey will work – where things like quality display, social and search will create more brand search in dark areas. That is the point of all this, right? Where you drive early stage media should result in growing brand demand, no matter how small the business. (2018 notes: media media media. Oi. That’s all that was available in 2014! Pouring all of your money in media is not the best tactic because it’s still averaging your customers.)
  3. The customer journey will NOT work in areas where weak existing and future customers exist. The customer journey is too costly and that will be the case for the vast majority of people and neighborhoods in the world. I know of many companies who maintain great acquisition cost in 1,000 or so ‘nooks’ but see 10x the cost in 10,000 ‘nooks’. Follow? Can you get past the 1,000? Sure but start where it is profitable. So, don’t average areas. Focus on the “A” areas first and once that has been settled, the “B” areas deserve your attention.
  4. Why location? Something I will write about in coming posts. A: Real social circles. I bet you are not walking out of your house today in a pink suit. Why? Social circles. What we do in social environments, both on and offline impacts our purchase behavior. Something that has been well know since IBM did the original heat maps in 1899.

In summary: Taking a first step in customer segmentation and media segmentation helps a lot. It might cut some audience and media spend but in the long run, it drives sales growth in a predictable and profitable way.

In early 2015, I revisited this article, so here’s some almost 3-year-old commentary:

1 Feb 2015:

I have been running into some very interesting media examples. Some media is being mixed together several chains down. A mix of low value media with high CTR ‘gamed clicks’ averages out to average CTR, filled orders. Rotten to the consumer and buyer, good for the ad network and a poor plan for the long run for all.

2018 final notes:

When you develop a good strategy, updating your tactics keeps it working. In 2014, media was king so we had to play the game. In 2018, we’re saying pump the brakes on media. You can spend money on the right media, showing to the right audience, using the right message. We know other ways to speak to your customers, and we can get you look-a-like customers too. Make 2018 your year.

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Why focus on happiness?

Customer delight is a form of happiness.  It is a well-documented, but a hard to achieve KPI. Jeff Bezos understands how important it is and has 5 teams working on it at Amazon. It’s that important. Why?

Customer delight is broken down into 3 key elements:

  1. Create customer loyalty. Instead of rebuying your customers through paid media, how can we get people back easier?
  2. More profits. Easy to say, hard to execute. While many businesses are offering discounts right away, having customer delight slows down the coupon bus. Apple does not have coupons, you don’t need them either.  
  3. Reviews. A customer who gets it, says nice things, online and to friends. They own it, flaunt it and you win.

According to a Bain & Company report on Net promotor score and profits, only 9% of organizations surveyed could sustainable profits and growth for 10 years. 9! NINE! I don’t want to look for a job that often.

A 5% increase in customer retention can yield 25% to 100% increase in profits.  

My focus for 20 years is finding ways to create customer delight and balance that with keeping you happy as well. An organization that is happy, along with its customers is a great place to work. But how can this happen in 2018? It seems so hard.  

For one, most organizations I know, hundreds of them so far, have very little predictive capabilities. Furthermore, very few have predictive down to the people level.  

When we install customer delight, the focus one the organization on the customer changes and the corporate culture as well. People, process and leadership align on balancing the customer with the employee.  

By linking customer delight to the core values and goals of the organizations connect people to profits in a positive way. When things are aligned, they move fast.

To learn more and see how we can help you, please contact us. We promise a call is worth the effort.

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The Road to Culture and Measurement

McKinsey Quarterly published an article titled ‘Culture for a digital age’ that confronts the importance of risk-taking within business in today’s quickly progressing world. The advancement of technology is driving cultural change forward so rapidly that if quick, calculated risks are not taken to match the rate of this change and the increasing demands of customers then the businesses that fail to do so will quickly fall behind.

Many top companies have approached this issue by distributing power to make important, impactful financial decisions more evenly across resources within and outside of the organization. Instead of these decisions being dictated primarily by the CFO as they were often done previously, a wider variety of employees on all levels and within multiple positions are given a say in how and where the company moves forward, as well as a hand in improving customer communication and relations.

“Customers increasingly expect companies to respond swiftly to inquiries, to customize products and services seamlessly, and to provide easy access to the information customers need, when they need it.”

While there will always be clear and inherent risks involved with giving that kind of power to so many people, many consider this is a necessary risk worth taking to keep up with both the times and the needs of current customers.

In another recent article published on Forbes in May of this year titled “The End of Advertising as We Know It,” contributor James McQuivey explores the issue of shifting standards of advertisement within society and how it’s impacting the companies that depend on revenue from it. The article states that customers are frequently finding more and more ways to avoid traditional methods of advertising online, and it’s this shift that is driving companies to switch over to a more personalized and communicative method of advertising. “That intelligent conversational relationship with the customer can begin now in chatbots on websites, in chat interfaces on mobile apps, and in Alexa voice skills.” McQuivey says.

“The technology will make conversations more satisfying to customers, but it’s just as important that marketers learn how to make those conversations sparkle with the brand personality the CMO has committed the company to.”

These methods are ultimately turning companies into what is looking more and more like a team effort within a business framework than ever before. A positive outcome is boosting morale and increased loyalty of the customer base, creating a dedicated, enthusiastic team of employees on all levels of the company. By utilizing these methods, organizations are able to create significant impact to all.

The challenge will be measuring segmented customer needs and delight before clicks, cookies and buying patterns. Without a framework that includes past, present and theories of the future, segmented by customer and product, more failure will occur at an ever-faster rate.

The good news: the leaders are investing in the future… and theories of the future. Amazon, eBay, Netflix and Disney all have predictive technologies under development or in use. This will take market share, stop weak competitors and solve customer delight, not because of technology but because they understand how to integrate data, customers and frameworks.

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The problem with offering discounts to first time buyers

This article was written by Madelyn Skinner.

The Story.

I am fascinated by subscription boxes, although a little overwhelmed, too. My friends are constantly talking about their monthly makeup boxes, their newest shipment of “ugly” food, a miracle face scrub, etc. in my curiosity, I found a website that aggregates many of these subscription boxes and includes reviews.

Two weeks later, I see an ad for this site on Facebook. It’s eye-catching: they’re advertising a monthly plant delivery service, and I absolutely love succulents. I clicked through. I rarely click though on Facebook ads. I look at the plant subscription service and then go to the main page with all the boxes, and before I get halfway down the page I get a pop up.

“50% off your first box with this promo”

The Dilemma.

What?! The box right below the pop up was a natural skin care box for $60 a month, with a value of $120, so I’d only pay $30 for my first one. Seems like a great deal at first, and I’m tempted. What’s the issue here?

I was already interested, but now they’re acting desperate. PLEASE BUY SOMETHING I’LL GIVE YOU A DISCOUNT.

Why do companies think they need to give discounts to first-time customers? I was already browsing intently, I could have been a customer! Giving me a discount on my first box is a mistake: it’s like I’m lured in through false promises. I’ll have to pay double the amount next time. If I am lured in by a discount, do you think I’ll want to pay full price? Not likely.

The Solution.

Here’s what to do.

Don’t rely on a discount strategy to lure customers. Stop assuming people will not order if they don’t have discounts. When you do this, you are averaging people who are already on the fence with people who could be your next best customers. But they’re turned off now.

Focus on your branding. What’s unique about you? Don’t sell yourself short.

Bucket your customers according to personalities. Maybe you don’t need to get as granular as diving up by ESTP or INFJ, but at least understand that people are unique beyond age group and income.

We understand why companies do this, and we want to help you. Give us a call, or write and we can help develop the right strategy to get the best customers.

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Marketing Budgets: Not as Hard as You Think

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.

  • Personality predicts desire. Desire drives decisions. Purchase decisions.
  • 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.