Data, Data Everywhere, not a millibyte to use
Do your buyers really know what they like and why they like it
“The actions of men are the best interpreters of their thoughts,” said the British philosopher John Locke.
And Economists such as Paul Samuelson took this to heart. Samuelson posited one of the most enduring lessons that I learned as a student of Economics - the empirical superiority of Revealed preference.
In simple terms, buyer choice reveals their preference.
But as marketers, we know this already. What is useful to us is the Why behind the behavior? What factors trigger buyers to make these choices?
“The Why” provides inspiration for product design, messaging, ad creatives, contextual media choices and retention efforts.
Enter, Data.
Now, consider these broad sources of data that a marketer works with today:
Most of us rely heavily on survey data without questioning its veracity. It’s easy and faster to commission, costs less (sometimes) and the results are easily interpretable.
It has its flaws though.
I use the below example to examine why I say this. Say you are interviewing customers of competition product. Now, let’s consider how they respond to this seemingly harmless question:
“What is the satisfaction level with your current CRM?” (replace with your product) Rate it on a scale of 1 to 5.
Your respondents' responses to this question are polluted by several biases.
Bandwagon effect: Most buyers, at least those in the Early & Late majority curve, don’t question the market leader at all. They are merely followers with a borrowed perception they carry from Innovators & Early adopters.
“I might not like it, but it’s still the best, right?”
Sunk cost bias: Effort, time, and cost your buyers invested in a product in the past do impact their present and future decisions.
“I have invested my precious time & effort in dumping data into this system. I am fine with it.”
Mere exposure effect: Your buyers have been most exposed to the market leader for years and for most of them, your category of products is synonymous with the leader.
“I am familiar with them, I like them.”
In sum, humans don’t “really” know what they like and why.
Bad news.
Usage data, whether Product usage or Website behavior is better but is better deployed for a narrower, different objective. Analyzing this data however comes with a warning - environmental factors that impact this data but are not visible might lead you to a stray path.
In fact, most data that we use today is devoid of inputs from the buyer's environment.
Their context.
I decided to challenge myself with a quiz.
Where is my product used mostly? Work or Home
On what occasions do my product get used most?
Is it an individual activity or performed with a bunch of besties?
Did we account for our buyer’s best days and worst days when designing the product?
Do they move their mouse differently when they have bad days? - jagged or intentional? Do they request for your AI assistant fewer times when they are stressed?
TBH, I am a bit shaky about my answers to these.
Understanding differences in behavior based on our buyers unique context, by cohort, is an often overlooked aspect of marketing.
Adding contextual data to your datahub is one thing, but deriving insights from this demands considerable judgment. When done well, it can have a far reaching impact on your product development, messaging, choice of the target audience, and eventually demand.
Think about it: The larger incumbents in your market have a more sophisticated and higher volume of both Survey & Usage data. They can hire better data scientists to churn all the data and come up with magical models.
Therefore, in a crowded market, your only competitive advantage is understanding buyer context better.
So, why do we underestimate the importance of context as a driver of behavior? -
Richard Shotton in his book, The Choice Factory, attributes this to:
The curse of rationality. It appeals to our ego to believe that we are paragons of rationality.
The “new-age marketer” of today is trained to hate uncertainty. Its as if she is told that uncertainty is unhealthy. And the cure peddled to cure uncertainty is “more data”.
However, More data
≠More useful data.
In fact, data has made us view our worlds as deterministic, even if that data lacks “that something”.
So, is there a silver bullet to glean buyer context and complement it with existing buyer so as to make decisions with 100% confidence?
No. The reality is that this process is messy, and needs multiple techniques to be stitched together.
Perform a day-in-the-life research with different cohorts of buyers, planting a visual map of their lives in your mind and how your product lives within their ecosystem
To get an aggregate sense, append the above data with some Search listening. And this analysis could very well imply a peak at the sub-conscious. It is truly useful.
There are a few good tools around, such as Answer the public.
The below map is for one of the hottest product categories today - Note-taking apps.
A quick glance reveals a couple of insights from this map-
Cohorts of users emerge
Based on their roles -“note taking app for programmers” and “note taking app for students”
Based on their device ecosystem - “note taking app for ipad”
Latent demand for specific capabilities - “note taking app with tags”, “note taking with links”
If nothing, you can use these as hypotheses to be tested when you perform that day-in-the-life research.
These are two ways how marketers could use insights from superior understanding of context-
Product marketers
Context: If you are a B2B marketer selling a product like CRM, you should know that most salespeople use this tool to dump their data during the last 4 days of the month, just in time before their next pipeline review meeting with their manager is scheduled
Problem statement for the marketer: How do I ensure that product use is distributed evenly across the month?
Action by marketer:
Voice-enabled data input for any time, anywhere
In-product gamification to create engagement & product love
Brand, Demand gen & Digital marketers
Context: That ad of yours was on view but wasn’t necessarily viewed
Problem statement for the marketer: How do I ensure I get a lift in my desired metric - brand awareness or lead volume?
Action by marketer:
Narrow targeting is fashionable because it seems efficient. However, your audience does not think as you do (there is a reason why premium publishers charge a hefty premium - “guaranteed eyeballs”).
See if you can perform this experiment:
a) Use publishers & Ad formats that optimize for high dwell time with ~15-20% spillover
b) Narrow targeting with minimal spillover.
I have been surprised in my career by how much more effective & efficient approach a) has been, from both a lead generation and cost of acquisition pov. And of course, there is the immeasurable brand impact because of the wider audience reach (call it spillover:)) that I didn’t account for.
It might sound counterintuitive but your audience thrives on that “media spillover”. So doesd your brand.
There are many such micro-contexts that we don’t pay attention to.
I’d even venture to say that the No.1 skill for the marketer of tomorrow will be to build the muscle to get comfortable with reconciling disparate data points from questionable data sources - qualitative and quantitative - build hypotheses, test them until they become a rule in your playbook.
Remember.
More data ≠ More useful data.