New-age Customer Acquisition with Retail Analytics

Technology | 7 minutes to read

29th Mar, 2019

Customer engagement strategy plays a pivotal role in defining the way marketers plan their interaction with their prospective customers, retain existing ones and help the brand adapt to changing tastes and preferences. However, this also means that there is an immense amount of data which needs to be captured to make sense out of the customer-product journey.

Evidently, the Indian retail industry is one of the fastest growing in the world. The pace of development is not just restricted to major cities but has also spread to Tier-II and Tier-III cities.


The pace of change is pushing the retailers to devise methods that predict changing consumer trends, their price points, their preferences, all this while the modes of consumption have increased manifolds for the consumers.

This has led to emergence and increased dependence on Retail Analytics which has enabled key decisions related to crucial activities like procurement, inventory management, point of sale engagement etc.

Irrespective of the category and size, retailers have come to understand that the secret of success lies in managing the right inventory volumes which do not allow the sales to get hampered, along with ensuring that you don’t run out of it during the peak times.

Retailers continue to use analytics to predict the demand, changing trends and stock accordingly to optimize their spends and get better at their procurement.

Today, retailers are not only restricting analytics to prune their operations but have started to use it to define the way they target the customer acquisition. Deep insights into purchase patterns, frequency, their search criteria and basis of evaluation, all this information is being used by retailers to personalize the engagement strategy with their customers.

It has helped the marketers to define the messaging with respect to choice of segment, choice of medium to be used and plan their marketing budget allocation more effectively. Allocation has become more ROI oriented with targeting getting based on demographics, habits, likes and dislikes based on information collected.

Despite plethora of information available about the customers, the critical point still continues to be the pricing. The science behind the price play like – when to bring down the prices, how to use pricing as a tool to navigate through the market challenges and how can sales be boosted through effective pricing strategy. With abundance of data collection backed by retail analytics companies are getting smart in the way they are handling this challenge.

Also, tracking customer footprints in the digital world is enabling micro analysis which is helping retailers to predict bundled sales i.e. which orders are most likely to be clubbed by customer or based on purchases which is the next purchase customer is likely to make.

This is also leading to increased awareness about customer purchase sentiments. How the customer responds to marketing materials, to product information (brochures/collaterals etc. ) and what kind of engagement gives maximum returns.

The future is going to see much more precision in terms of predicting and forecasting. Companies are investing heavily in the infrastructure to ensure that they have the right kind of software, tools and methods to be able extract data from all the possible channels of engagement.

The richness of the data along with the precision of predictive analytics will be the key to critical decisions that will help the companies in optimize their resources effectively, efficiently and continue to engage with customers in a way that the brands become part of the customer lifecycle.

This article was orginally published here.

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