Using Predictive Analytics For Individualization in Retail

Predictive Analytics has put a strong footing in the retail sector where companies are able to understand what their customers want, what products are in demand and are able to allocate their resources optimally. Going a step further, this very analytics is beneficial for targeted marketing to an individual level. Yes, individualization via predictive analytics is the biggest boon that companies can use to their advantages. Achieving the most granular of data today is possible and such multiple endpoint creations help in providing a customized solution for individuals instead of putting them under a group.

Why Individualization?

The huge wall between physical and online retail stores has fallen due to rapid digitization. With Omnichannel marketing strategies and by utilizing predictive analytics, a company can find what a particular customer requires. Their past history and behavior help in predicting what they might want or what more can they be offered. Individualization helps in narrowing down the possibilities of product attributes and can be presented as per the user’s data.

For example, if a person is constantly trying to look for a particular color or is worried about size, the retailer’s website can show them such options instantly. These can be even used for personalized emails or messages that can lure them to a nearest retail store.

Making the Most of Predictive Analytics

There is vast information available that can be used in different ways to implement predictive analysis. Retailers can tap into it and use it in the following few ways to make the most of it.

1. Improve Targeted Marketing

Individualization in a way invokes ‘a feeling of being special’ in the users. At the retailers’ end, it merely helps in offering these customers what they would purchase, understand their styles, trends, and sum up a personalized service. It can be even leveraged to understand what they want so that retailers can try to acquire or create a new segment of products for the same.

2. Keeping Them Interested

In today’s time and age, the pool of information for both retailers and users is so much that they can be lost in it. Customers are quick at switching from one retailer to another when they do not get what they are looking for or find things uninteresting. Using predictive analysis can definitely reel new customers but at the same time, it will keep them engaged. Retailers are able to sense if the customers are staying or leaving by simply surfing or checking the purchase history. Such actionable intelligence can push the retailer to bring back the customer by throwing incentives or providing offers that are based on their data analytics. Also, such data helps in keeping the current customers engaged by sending them timely offers and planning appropriate promotions.

3. Physical Store Value

User data analytics such as demographics, financial market conditions, and recent customer purchasing history can be used to understand where customers hang out the most. Although here it is more of a group analytic, such a data can help retailers to understand where to open a physical store location. Once the store is in place, individuals can be lured via various offers to a place where they prefer to visit.

4. Offering Better Customer Service

Predictive analytics helps the retailers to come up with a better marketing plan. Based on their individual data such as their interests, purchase history, likes, and dislikes, retailers can help them make informed decisions. Also, offering query resolution at individual levels makes the customers feel valued and can retain them in the long run. Such smart analysis will also help in using social media marketing to the fullest of potential.

Predictive Analytics for individualization can be used as the ace in the already swarming pool of marketing strategies. Get in touch with us to understand how predictive analytics tools can help in maximizing the potential of such huge data gathered and reach out to your customers better.