We are all familiar with applying analytics to sales data.
In the most sophisticated cases, big data might reveal surprising aspects of
our sales process; a notable example is from my employer correlating weather
patterns to bakery sales and concluding that cake sells well during a drizzle,
while grilled cheese sandwiches are especially popular during a heat wave.
These types of analyses can help refine our products and
sales processes in fairly obvious ways. What’s also interesting, and perhaps
less well utilized, is using big data before a sale even occurs.
A recent example of this is a major automaker that started
using its vehicle configuration tool before a new vehicle was released. (If you
visit any automaker’s website, you’ll likely be able to use one of these tools
to pick a model, change colors and options, and view a rendering of what your car
will look like.) This automaker’s configuration engine was populated with several
options and colors that were not slated to be available in a particular market.
A color that surveys and sales analysis told them would not be popular, and one
that was not planned to be an option for the car, was one of the most popularly
configured colors. The automaker changed its production plans to make the color
available, and it later became a hot seller. In some ways, this dovetails with Henry Ford’s famous quip that if he’d asked customers what they wanted, they
would have asked for a faster horse.
There’s nothing new about applying analytics to surveys and
customer input, but combining this with tools that let customers visualize and
customize products is a less intrusive and often more accurate way of capturing
While 3D modeling engines and complex product configurators
are likely out of reach for most companies, capturing customer feedback at the
point of interaction and using that feedback to drive analytics can accomplish
the same function.
Rather than sending out the millionth “Congratulations,
you’ve been selected to participate in our 198 question survey!” email,
give your customer-facing employees an easy way to capture what they’re hearing
from their customers. This could be a simple form that’s captured and collated,
or a website where customer feedback can be easily captured. More sophisticated
options include hover and click analysis on product imagery or big data analysis
of social media chatter.
The technology is less important than the fact that you’re
gathering customer feedback before the sale, and doing so without the customer
knowing they’re formally providing feedback.
Capturing and analyzing customer feedback in an informal
manner, and doing it outside the context of a current product, is a great way
to leapfrog your competitors, especially when combined with emerging analytical
and big data capabilities. While the market is trying to determine how to
create a faster horse, you can be perfecting the automobile.