Data, Data Everywhere, not a millibyte to use
When your buyers don't 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. The concept of the empirical superiority of Revealed preference was the most enduring lessons that I learned as a student of Economics.
In simpler 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” is the 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 marketers lean on survey data without questioning its veracity. It’s easy and faster to execute, costs less (sometimes) and the results are easier to interpret.
But it has its flaws.
I use the below example to examine why I say this. Say you are interviewing customers who use your competition. Now, let’s consider how they respond to this seemingly harmless question:
“What is the satisfaction level with your current product?” Rate it on a scale of 1 to 5.
Several human biases collude to pollute your buyer’s response.
Bandwagon effect: Most buyers, at least those in the Early & Late majority curve, don’t question the market leader at all. By definition, they are followers with a borrowed perception carried from Innovators & Early adopters.
“How do I evaluate it, 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 heard about the market leader for years and for most of them, your product category is synonymous with it.
“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 of higher quality but is better deployed for a narrower and a different aim. Analyzing this data, however, comes with a warning - several “buyer environmental factors” impact this data that is not visible to you. It might even 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 the worst days when designing the product?
Do they move their mouse differently when they have bad days? - jagged or intentional? Does a stressed-out user request for your AI assistant fewer times than average?
TBH, I am a bit shaky about my answers to these.
Adding contextual data to your datamart is one thing, but extracting insights demands considerable judgment. When done well, it can have a far-reaching impact on your product development, messaging, choice of the target audience, and 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.
As “new-age marketers”, we have been trained to hate uncertainty. As if uncertainty is unhealthy. And the cure peddled to cure uncertainty is “more data”.
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 the buyer context and complement it with the existing buyer data so as to make decisions with 100% confidence?
No. The reality is that this process is messy, and multiple techniques need to be stitched together to arrive at useful insights. Here is a couple of them that I find useful:
Perform 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 peek 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 product 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 of how marketers could use insights from a superior understanding of context-
Product marketers
Context: If you are a B2B marketer selling a product like the CRM, you would know when your audience uses your product. 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.
Depending upon the industry you operate in, the results could surprise you. In my experience, a) has been a more effective & efficient approach, from both a lead generation and cost of acquisition pov. And I don’t even include the immeasurable brand impact because of the wider audience reach (call it spillover:)).
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.
The No.1 skill for the marketer of tomorrow will be to build a new mental muscle. Get comfortable with reconciling disparate data points from questionable data sources - qualitative and quantitative - build hypotheses, and test them until they become a rule in your playbook.
Remember.
More data ≠ More useful data.