Much has been written about big data; the importance of deploying analytics in marketing efforts and the trove of untapped information companies have available to them. But rather than focus on how much of an obstacle it can be trying to interpret big data, I want to discuss how you can make it actionable.
If you’re a marketer, chances are good you have visibility into marketing-related data, such as who you targeted for which campaign, who responded, and who purchased which of your products. But today, that may not be good enough to develop deeper understandings about your customer.
Take for example: product return information. If you had a customer who purchases five pairs of shoes every six months, that person may be considered a great customer. However, if that customer consistently returns three pairs within a week of purchase, he will not be as good as you thought.
Besides returns, other types of information retailers may want to look for is financials or account status. As an example, knowing that a customer bought $100 worth of product from you is part of the picture; knowing that customer purchased it using a store credit card and has been making monthly payments tells you more. Having information on returns, financials and account balances allows marketers to draw a more complete picture of a customer.
What marketers should be doing is partnering with their IT counterparts to see what other data is available that can be integrated into a marketing database, to develop a holistic view of your customers. Also talk to your vendors, partners and agencies to see what additional customer-level data can be passed back to you.
The next source of information could be the unstructured data that is available within your organization. Examples of this would be customer emails to the company or in some cases, compliments, complaints or questions directly from a website or recorded call center conversations .Marketers can gather and collect these unstructured data and identify intent/sentiment/behavior or issues.
There are existing technologies such as text analytic tools that go through written texts and parse out the text, to derive insights from the content. Marketers can gain understanding around intent and motivation, and can identify whether there is an opportunity to market to certain consumers -- or send up a red flag to address an issue in order to keep them as a customer.
External social media channels provide motivational and behavioral information that’s not readily available in traditional transactional databases .What I mean is that transactional data only provide information on what was marketed, who responded, and who made a purchase. What the transactional data don’t really have is why a consumer bought something or why they responded, or why they didn’t. This type of information can be found through social media sources.
There are proven social media analytic solutions that makes it easy for marketers to listen to and understand the voice of the market. However, one challenge in working with social media data sources is that it may not be easy to tie in individual tweets or feeds to an existing customer record. But they do give marketers a sense of what general market sentiments are around your products, brands or organization.
So while this is all food for thought, I’d also issue a caveat; that it’s important for marketers to avoid going overboard by getting data for data’s sake. I’ve heard that termed as ‘egometrics’ – meaning: what purpose does this data serve other than to possess it? One of the guiding principles of deciding to pursue a certain type of data is, at the end of the day, does it help you target your customer better? Or does it deliver more personalized interactions? And finally, how can you leverage the insights to move customers through their buying journey? The ultimate goal is to better engage your customers by delivering great experiences throughout the entire journey, and cultivate customers to become loyal advocates for your company.
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