It’s long been established that good marketing goes beyond customer segmentation. Businesses need to transition from segment-based marketing to more personalized customer interactions.
Most marketing actions have an ultimate objective of either customer acquisition or customer retention. Which action to select and how to implement it depends on the product that needs to be marketed and the revenue that is desired, and of course the quality of business analytics providing the insights.
A decade ago, segment-based marketing was all the rage. Based on empirical analysis, businesses would allocate customers into pools for targeting their marketing campaigns.
To some extent this worked well, but a more personalized approach is needed to fully exploit the customer base. In the past it hasn’t been possible because either the data was outdated, or advanced analytics weren’t in place to sufficiently process the data and make reliable recommendations.
Businesses need to harness massive amounts of data that customers generate to effectively micro-segment customers, analyze sentiment, predict behavior, personalize offers and cross and up-sell in real time, across all channels. Through sophisticated analytics, businesses can dive deeper and become more specific with a targeted approach.
With the right analytics, businesses can precisely select customers and products to facilitate tactical and strategic decision-making, which will positively impact their revenue. In fact, McKinsey states that a company using big data to the full could increase its operating margin by more than 60%. High ROI is a key performance indicator that undisputedly separates the good from the bad marketing choices.
No mater which specific approach is chosen, marketing managers need to know which customers have revenue potential and which products are most likely to be accepted by each individual customer. On the basis of this invaluable knowledge, marketing managers can proceed to execute a campaign, and should be able to calculate up-front the cost of the campaign as well as its ROI.
Beyond segmentation, a businesses ability to optimize conversions and calculate customer scores with respect to propensity-to-purchase is essential for targeting. Individualized scoring quantifies a customer’s propensity to buy the offered product and can indicate whether the candidate should be marketed to, or not.
We see great potential for customer-facing businesses that adopt big data and personalized customer analytics as a platform for growth. What are your thoughts on big data, micro analytics and marketing insights? Feel free to share and add your comments below.