Corporate marketers may think they've found a way to draw the best value from big data, but in reality, that movement is only now beginning. The possibilities with data are endless - by gathering information from their clienteles about their incomes, spending habits and the ways they respond to advertising, corporations can find better methods of engaging consumers to improve sales of myriad goods and services.
Of course, data quality is the prerequisite to this entire movement. By using address management solutions to verify the mailing addresses, email addresses and phone numbers of potential customers and organize their clusters of data, companies can ensure that the information they're working with is proven and actionable. From there, marketers can proceed to optimize their advertising campaigns for generating the most revenue possible.
There are many questions that marketers must ask before they can leverage big data to achieve the best results. Here are a few issues that remain unresolved.
What consumers should be targeted?
Forbes raises an interesting question - is it possible for companies to over-target their target demographic? Even if you've honed in on one particular group that will most appreciate your product, might it also be important to branch out from that group? Say a footwear company develops a skateboarding shoe and determines that 60 percent of their sales will come from teenage boys. That doesn't necessarily mean they should target only that group. They might also generate plenty of business from older buyers, or from moms buying shoes for their kids. By using big data to overemphasize target demographics, companies might actually miss out on potential sales.
Can data be mined openly and honestly?
SAP points out that one challenge for marketing companies is collecting data from consumers without being "creepy" about it. There are countless avenues these days for corporations to collect information, including social media sites, e-commerce sites and other places where people share their personal information online. Gathering all this info might seem efficient and ultimately profitable, but it could also be unethical. The best approach is to be honest and forthright with people, telling them when, where and how their personal information is being collected. Tricking them is the wrong approach.
How can companies test their theories?
According to Forbes, marketing directors' two favorite words are, "What if?" Rather than eyeballing clusters of data and devising theories based on the numbers they find, marketers prefer to take a hands-on approach and devise tests to answer their hypothetical questions. If an executive thinks of a marketing strategy that might help improve sales, he or she is likely to draw up a simulation that will measure its efficacy in a controlled environment. In order to maximize the utility of big data, marketers should work to perfect their simulation models, working with analysts and technicians to devise better tools for testing their marketing strategies.
What are the limits of statistical analysis?
No matter how much knowledge marketers are able to glean from big data, they must remain aware that statistical analysis has its limits. In short, the problem is that different factors interact with each other in ways that can be unpredictable and counterintuitive. This is visible in many fields, not just marketing - statistical trends can be based on irrational whims that can't be measured or predicted. Because of the difficulties of statistical analysis, some companies have turned in another direction, choosing to build data models that interpret both qualitative and quantitative factors, which is a far more realistic way to simulate the marketplace.
Data analysis can do a world of good for marketing companies, but before they enter into that realm, executives should make sure they're moving in the right direction.
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