Market segmentation is certainly not a precise science. Majority of marketers get as far as “first-time users” or “regular users” when it comes to narrowing down their segments. These segments, however, are exceedingly broad and hold the potential for multiple subsets such as first-time users who are devoted to classical music versus those who are sports fanatics; and regular users who spend their weekends with the Xbox as opposed to those who are bringing up families and attending their kids’ baseball games.
Marketing success stands or falls on the messaging strategy you apply to each of these subsets. Using sports analogies with Mozart lovers will not help you tug the right strings. Likewise, handing out free opera tickets when sports fans sign up for your yearly subscriptions will make you come across as snobbish and irrelevant.
Big data analytics can overcome these segmentation challenges and let you target customers at a granular level with tailored messaging that your audience can relate to. The wealth of data at your disposal will let you zoom into what your prospects are viewing online, what they are following and liking on social media, their buying history, and particularly whether any of these activities are indicative of buying behaviour. This means that you can shell out fewer bucks to market to a smaller group, while enjoying a surge in your conversion rate. Moreover, this kind of intelligence will allow you to cross-sell effectively and enhance customer lifetime value.
However, to make the most out of big data analytics, it is essential to ensure that business users have clear visibility and tighter control across the analytics lifecycle, avoiding delays that typically arise out of relying on IT and data scientists to deliver results. Sadly, the current state of big data platforms includes an assortment of specialized tools that run in silos and perform specific functions, causing marketing teams to become dependent on highly trained specialists. An end-to-end self-service platform is called for that can equip business users and their data analysts to play with data and accomplish elaborate segmentation tasks – work that in the past could only be carried out by specialized data scientists with PhDs.
In a recent example, a global technology products conglomerate struggled to create micro-segments with their incumbent marketing automation tool which was simply incapable of handling massive amounts of data. They turned to big data analytics for their marketing campaigns which resulted in a whopping improvement in conversions through narrower customer profiling combined with personalized offerings. Since they used a self-service big data analytics tool, they successfully ended their dependence on the IT team to slice and dice customer data. Despite complex segmentation rules, the marketing team was able to easily fine-tune segments to reach out to the right audience and further use a feedback loop to improve data models and select optimum contact lists. The move helped them save substantially in terms of data preparation costs and allowed their marketing team to focus on advanced analytics instead of tedious technical details.
If you want to learn more about how you can harness the power of self-service big data analytics to streamline demand generation and greatly enhance your revenue, request a demo today.