Technology can be wonderful, I’d be the first to agree.
Much of what is new in customer relationship management (CRM) and the area of gathering and utilizing customer data could not have been done just three or five years ago. But recent advances in software, communications, and processing power have made possible a new world of data. Over the next several months I’ll look at these advancements and talk about how they make a difference to marketers.
But technology is not, IMHO, the place to start the conversation about customer data. Instead we’ll start with a marketing conversation.
The best technology in the world is still limited by how the marketer uses it. “Garbage in, garbage out” is still the truth in any data collection context, and the most difficult decisions are the choices we must make about what information to collect and the appropriate ways to use it.
At the start of any new data collection exercise, the temptation is to collect every single data point we can think of. We are not exactly sure how we will put all that data to use in serving our customers or interpreting our market; but since we don’t yet know for sure which customer characteristics have what impact on consumer behavior regarding our offering, we want to know everything.
With the power of today’s computers and the richness of current database software products, you can store all the information you could ever want, so why not collect it all?
We’ve all made that mistake at least once and lived to regret it.
Data collection may be a straightforward process, but data analysis and manipulation are time- and bandwidth-intensive tasks. And too much raw data can be overwhelming to the marketer inexperienced with its interpretation. Instead start small and be focused, allowing for expansion as you learn to work with the data you have.
Data analysis is an art and a science, and though the science of it is critical, so is the art — determining which information holds the greatest business significance and can offer the most competitive advantage. This determination will differ with every product and service, and it will take into account various realities, including sales channels, overall market size, market penetration, brand awareness, the point in the product’s or category’s life cycle, and every other aspect of marketing information.
Lest any among us fear that technology is diminishing the need for highly skilled marketers, an exercise in establishing criteria for determining which data to collect and analyze will stop that fear cold. There’s still a crying need for marketing insight from analysts and market watchers; the individuals involved in making the judgment calls about which information to collect desperately need that insight.
So how do you begin to lay out a data collection strategy?
- Start by taking a look at what data you now know.
- Then consider the assumptions your firm works with that shape marketing and sales strategies.
- Ask yourself which of those factoids are adding value to your marketing efforts and which seem extraneous.
- Explore with your sales force and/or third-party sales channels what they need or would like to know to help close a sale.
- Find out how your product development folks are thinking about future markets; you need to see what assumptions might merit testing.
Capture all of these thoughts, and anything else that applies your particular market situation, to develop a credible picture of your market today and in the predictable future.
Having a clear read on what is already known (even if it’s known informally or is not yet shared institutional knowledge) gives you a really good lead into what data to collect first. The more time and energy you invest in getting a clear picture of your market today, the better job you will do later in data analysis.
So for those looking at building a data analysis program, I send you off with an assignment to start this process internally. And let me know how it goes.
Next week I’ll look at examples, from our clients and from you, of how some businesses have tackled this challenge.
If you sell or market data analysis solutions, feel free to share success stories about how your clients have addressed these tricky issues of selecting the data to track. As long as you resist the temptation to send a blatant sales pitch, I’ll be happy to share success stories, tips, and tricks.