Over the years, we have witnessed different kinds of marketing strategies, all aiming to reach and attract more customers. Very often, these strategies involve marketing offers meant to entice customers into redeeming them, promoted either by the manufacturer or the retailer. Sometimes, both retailer & manufacturer come together to run a promotion for any specific brand. More recently there has been a lot of chatter about targeting shoppers through behavioural marketing. This is the practice of studying the purchase history of the customers or their behaviour and then targeting special offers to them based on the findings. Again, under behavioural marketing once you have identified the target population, the offer would remain the same for all customers. That is, the incentives will be uniform for all customers.
So, how does Personalization differ from this? In personalization marketing, there would be a customised message delivered to individual customers unlike common communication which is practiced in behavioural marketing. In Personalization marketing, the process is automated by software that would design the individual messages. Hence, it is heavily dependent on the latest advancement in IT.
Consider a scenario where such exercises become more relevant. For a retailer, he might get requests from different manufacturers to give offers to their customers, say in every quarter. This can be a real challenge for the retailer. Let’s assume that there are 5000 brands up for discounts. The first step is to identify the right shoppers who would respond to the different offers. Usually, a propensity model for each brand would have to be built and we might therefore require some 5000 scores to run this campaign. Again, these scores could be transformed to customize the offers. The transformed scores could be based upon life-time value of the shoppers, i.e., the amount the customer spent for the promoted brand for the last few years. Also the shoppers could be segmented based on the customer’s recent visits, frequent visits, and the amount that the customer has spent, and so on. Once we have identified the shoppers having a higher score in these parameters, we can customize the offers to different segment of consumers based on these updated scores.
Nowadays, most companies have started using personalization techniques. However, it is the internet-based companies that leverage personalization to the maximum. Internet-based companies use software to maintain the records of customer transaction, and deploy tracking cookies to learn more about consumers’ other shopping interest. Using this data, a corporate website can personalize a visitor’s experience by showing them a customized page, featuring their language preference and products they are more likely to be interested in. The most popular example is collaborative filtering techniques adopted by major online retailers for personalized targeting. In simple terms, when shoppers A & B like Brand X and shoppers B & C like Brand Y then it is more likely that shopper A would prefer Brand Y. Information from different databases are put together to find the preferences of shoppers (deduced from the customers’ common interest from other shoppers).
The above shared image is an example of predicting the users’ scores using collaborative filtering. The scores for the products are determined, and then the system is designed to infer the purchasing behaviour for the unscored customers using the existing scores of other customers.
In addition to customer personalization, manufacturers adopt product personalization for the consumers. Many manufacturers invite customers to design tangible products to understand their attitude towards the brand. Product personalization is a popular marketing strategy that has been adopted for several years.
Personalization requires a lot of information to target the right shoppers. This information is used by software programs to send instant messages that are suitable to each shopper. Many companies have delivered such personalized messages through digital media that include mobile, internet, emails, and so on. Retailers have developed system that generate real-time messages for shoppers as they checkout at the point of sale.
This new approach has increased profitability for both the retailers & manufacturers by improving sales lifts that yield higher ROIs and increased brand loyalty.
Please read the following blogs for more information on personalization.