The expectation of the consumer has changed dramatically over time according to the nature of retail. Now customers before buying product look into the company, quality and check whether the product meets their increasing expectations. Thus ‘Customer Segmentation’ comes into picture when retailers arrange their broad customer base into smaller subgroups. To achieve this, retailers must first do away with the one-size-fits-all approach when interacting with customers and adopt a more personalized strategy.
So, this scenario brings customer segmentation for retail into action.
Segmentation of Customers Individuality
When the business begins, retail customer segmentation sorts individual customer into groups based on age range, products purchased or location. This way, they make a group of similar customers. Once you’ve established overarching groups, you can break those down into smaller, more specific categories.
Customer Segmentation helps retailers to insight into the specific grouped customer base. This makes marketing, product development and customer service more effective. Without the introduction of customer segmentation, the customers are generally grouped together. Doing this, business often struggles to meet expectations. Sorting them into segments reflect more a better business distribution.
Also, Read | How to use Reinforcement Learning in Marketing?
Customer Segmentation Data Improves Business
Segmentation gives retailers insight into their performance in markets. For, instance sales-related metrics, marketing campaigns, and incentive programs are broken down into segments based on the customer’s transactional data. Now, most cloud-based POS solution automatically syncs the information of customer transaction across all retail location and connected devices. Moreover, they also record them for further use.
We can create a model which keeps track of each customer’s interaction with your stores. For every purchase, the model generates the report, return, and sales order for easy analysis. We can take in accord of those certain items in store which are selling more frequently than others using the created model. Also, we can check which customer is more inclined to buy those items. Suppose, if one customer group is underperforming, we can create promotions targeted towards those shoppers.
This information can be used in a different number of ways by retailers. It can be possible by checking customer segments:
- Largest transaction per visit
- Profitable customer over a period of time
- Highest transaction frequency
- One-time shoppers or frequent buyers
- Reoccurring shoppers
By tracking the activities of the customer in groups retailers can look at a number of different ways. This helps them to attract new customers, build brand loyalty and create awareness around specific products. And give out rewards, incentives, and reminder to existing customers by encouraging them to use their resources.
There are some popular customer segments used in retail marketing
- First purchase: Companies look at the first purchase and make a prediction about customer future activities. Segmenting this data give an idea to retailers about customer persona, price sensitivity, and attachment of customer to a store.
- Acquisition: The individual customer learned about the retailers through online or offline channels, by giving social media promotions, word-of-mouth referrals, random walk-ins, acts as outboard skills which sharpen the businesses.
- Location: Companies often look at the factor of postal codes and distance from the closest store to the customer to make a number of predictions.
- Gender: Men and women tend to have different shopping patterns, needs in buying a product. Which helps the business look at these patterns and came up with effective marketing tactics. This Segment helps in promoting male and female-specific products online.
- Age: Retailers can make a number of predictions about a customer based on their age.
- Devices Used: It will give the retailers an idea about customer buying product online, so it categorizes customers in different categories. For, instance if your site is more popular through a web browser or mobile devices. This helps retailers learn more about frequent stores they visit.