How Big Data Helps in Smart Customer Targeting?

big data for customer targeting

Marketers have moved forward from traditional ways of marketing. With the advent of digital marketing, every step of a customer journey can be analyzed. And the accuracy level of customer engagement has improved with the help of predictive analysis, one of the big data techniques.

Methods of identifying the right target audience vary from one firm to another. However, big data analytics has made it easy yet time savvy.

Previously heavy research was used. The approach was to look into past performance and comparison of campaigns. Given the amount of content/data is produced daily, only the most efficient and well-crafted reaches out.

According to stats, only 5% of the 90% of the branded content garners attention. Rest goes unnoticed. What’s the reason behind? Consumers can consume only as much as they can. Demand stays the same whereas production is more.

All kinds of data produced and kept in record every year, collecting and analyzing such information will give business insight into what sells the best. Even such data can be used for making future predictions based on old customer behavior and patterns.

Big data can’t be used without structuring

Data without assembling is just a mass of unrelated information which can take years for comprehension. Here comes the big data and machine learning techniques implementation. Big data experts can help businesses structure data and use it for better insights.

Cut down data size, add filters

First step in smart targeting is determining what we need and exploring all sources of our user’s interest. In the second step comes cutting down data size and narrowing the search.

Narrow your options until you reach the exact proportion. For this, you can add a variety of filters. One basic could be time limit. If you just want results for last week, or even the last over, there must be a filter.

Analyze and develop a good understanding

Without stats, you may never know what your customer want. After filtering the right information, comes the part where we turn filtered information into manageable yet productive insights.

Advanced analytics in big data analytics help brands in many ways. Such as, business owners can look into associated words for known brands. Or we can see big influencers on Twitter, Facebook etc. making an impact for a certain brand.

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