This is your customer…some assembly will be required.
Using data points, there is a fairly reliable formula for anticipating what your customers want from you. However, your formula is only as good as the contents you add to it — so choose wisely.
Data can set a promotional campaign free, or it can paralyze it. Collecting data isn’t hard. What’s difficult is figuring out which insights are most effective for understanding the customer.
And really, it comes down to just a few. Like the rebar in a bridge or the bourbon in an Old Fashioned, the quality of just one core ingredient can determine the outcome.
Indeed, I believe any merchant can reach its desired customer base through fewer than 10 data points. The trick is knowing the best ones for you. I’m sharing eight of my favorites.
Here are the 8 data basics that will add up.
This list may not work for everyone. Each company has its own secret-sauce variable that factors into its data set.
But whether it’s a bookstore that has deduced its customer reads bodice-rippers and economics books, or a fuel station singling out luxury cars that take premium, these data points should help you create a good formula.
1. The correct name, even if it’s 1,000 characters long.
A few proper nouns, properly spelled and properly pronounced, are the basis of the formula.
Not only is a full name a good unique identifier, but research has shown people pay closer attention when addressed by name.
At a time when digital communication is replacing human contact, it’s a safe bet that using one’s name in texts or emails has a similar effect.
Keep in mind that it goes both ways. The recipient will more likely respond favorably to communications that sign off with your sender’s name, not just the name of your company.
2. Communication preferences…to avoid being “that guy.”
When customers visit a website, enroll in a loyalty program or take advantage of a promotion, they should be allowed to set barriers.
Ask how often and through what channels they want to be engaged. Doing so improves the chances of getting that customer’s attention. It also reveals much about that customer’s path to purchase.
Someone who prefers texts is probably mobile-reliant and busy and would respond to location-based promotions.
- Fun Fact: 90% of consumers open a text within three minutes, and 45% respond.
3. Physical location helps take the wondering out of wandering.
Customers tend to spend money where they spend time. This is why mobile location data, which can store a customer’s path via GPS or other applications, is estimated to be worth $12 billion.
However, while movement enables real-time communications that feel relevant — use the name! — never underestimate the value of the home address.
It hints at demographic characteristics as well as household occupants. It can, for example, indicate if an adult kid has boomeranged home to join the teenage one.
4. What they buy, to reveal lifestyle and interests.
Ever notice when driving through a neighborhood that the landscaping and vehicles are similar? What we buy says a lot about us.
One might purchase Star War figurines for his kids, or because he is a collector. Now expand what a customer buys to the neighborhood because neighbors tend to have similar lifestyles and social interests and therefore copycat preferences.
Community data can point to whether people are more likely to renovate their homes (because others have) or spend their leisure time boating. Data firms can sell these “lifestyle cluster” models.
5. Track their other “social” activities.
Retailers and brands know that “super fan” followers on their social media platforms encourage sales through word-of-mouth and influence.
They also leave a telling trail of bread crumbs that lead to other merchant accounts they visit. Consumer social media activity, and messaging, also can indicate financial stability.
Research has correlated social media use with consumer confidence, concluding that daily and monthly estimates of confidence can be reliably made months in advance.
6. How frequently do they come back?
Customer frequency is influenced by the goods. How many times does a person buy a boat or a hammock? But the overall “shelf life” of a product sets the clock on predictive behavior.
If the purchase cycle suddenly variates from the norm — a weekly supermarket shopper is now coming in three times a week — the timing of visits and category purchases should explain why.
That shopper may have changed her commute and now makes several small trips versus one big one, or visits simply to hit the store’s new coffee bar.
7. The story behind the money spent per visit.
Yeah, the size of an average transaction separates the big spenders from the small ones, but it also reveals price sensitivities.
A shopper may have a set budget of $200 per trip but will experiment with differently priced brands within that budget. Or the shopper may be willing to pay top-dollar for wine but not cheese.
The average transaction value can be applied to individual reward program members or to all customers. The latter measure, reached by dividing total sales by the number of transactions over a period of time, suggests if prices are too low, too high, or that promotions need adjusting.
8. The preferred channels.
Globally, people who shop across channels spend 30% more, and where these interactions occur can influence purchase amounts in other channels.
For example, research shows that 63% of all shopping starts online, so promoting a sexy new brand on a preferred digital channel could encourage customers to try something different.
In-store shoppers, meanwhile, are more likely to make an unplanned purchase in the store — 40% versus 25% online — perhaps because they remembered a forgotten item. So a targeted message on a preferred digital channel could lead to more purchases in the store. (I love symbiosis!)
Know Your Goals, Know the Best Data
There are so many other details data can reveal.
For example, the fact that the customer now works from home and therefore needs to dial down the wardrobe. Or, your customer is a gamer…but of only specific genres. Perhaps your customer is suddenly following a more organic diet.
Each merchant will need to refine the data that makes the most sense to achieve its predetermined goal. So formulate which data points you need first. That’s the first step to demystifying the consumer. It’s the first of many steps that will lead to higher lifetime customer value.
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