In today’s age of consumerism, marketing plays an important role of creating awareness, driving consumer engagement and growing businesses. Leveraging the right targeting techniques has become the most crucial factor for building and sustaining sales. From a retailer’s perspective, one of the key challenges is to identify market segments that hold potential customers for their products.
Consider this: Over the past decade, retailers have increased their marketing expenditure by more than 15 percent. However, this has not translated into proportional increase in business in terms of new customer acquisition or sales. For example, Mc Donald’s – one of world's leading food service retailers – has increased their marketing expense by more than 15 percent in the last six years; however, the overall revenue grew merely by about 12 percent. One of the key reasons for this is that marketing campaigns are not targeted to the right set of audience, taking into account their buying behavior – which in turn leads to lower than expected response rates.
An efficient audience targeting will enable retailers to identify various segments with their influential decision parameters and design the right strategy to maximize response rate for a given a campaign budget. But how do we analyze millions of behaviors and their billions of transactions distributed across multiple channels, to figure out the audience base who are most likely to respond to a campaign? This is the biggest task when it comes to targeted marketing.
An advance in computing has swept away media distribution barriers, releasing a Pandora's box of new content. The resulting fragmentation has shattered the notion of the mass-media consumer, forcing marketers to use hard quantitative data and analytical techniques to find and reach their audience.
Targeted Campaign by Uplift Model
The benefits of targeted marketing are two-fold: one, the total cost of marketing and acquisition decreases, and two, a well targeted campaign increases the likelihood amongst target audience to respond. This leads to enhanced response rates and Return on Marketing Investment (ROMI).
To effectively target the right set of audience, it is imperative to know the different segments. Broadly, on the basis of campaign response behavior, target audience can be segmented into four exclusive segments:
- Responded because of an action
- Responded regardless of an action
- Did not respond and no impact
- Did not respond because of negative impact
Analytically, there are different techniques available to target customers in a campaign scenario, but the Uplift Model is one of the most efficient and graceful ways to target customers by addressing the needs of different segments.