Blog : How Retailers can win customers by leveraging data-driven personalization
Today’s retailers can no longer depend on mass marketing and operations, as consumers are living in a highly personalized world. The consumers conveniently ignore any irrelevant offer no matter how attractive. To grab and keep their attention, retailers need to focus on the “individual consumer preference” and offer personalized experiences.
- How do you attract, keep, and re-acquire the most profitable customers?
- How do you know which marketing initiative and customer segments are the most profitable?
- Are you able to see which geography or age group represents your most loyal customers?
- Is your technology enabling the organization to create optimized marketing campaigns for better customer experiences?
- What if you could create a marketing strategy to cultivate a customer base that proves more profitable than last year’s customer base?
Marketers are continually looking for new opportunities to interact with their customers and deliver meaningful and highly engaging customer experiences.
Customer segmentation and personalization are an essential part of building an understanding of the unique needs of customers, especially when each one of them is at a different stage in the journey. While both terms are related, they are notably different. Segmentation will allow retailers to move closer to one-to-one, hyper-personalizing content for each a customer-type. And, by grouping the customers, segmentation makes personalization more manageable.
Together, personalization and segmentation can help retailers deliver on their promise to:
- Give customers more relevant, useful content
- Boost brand loyalty
- Seamless, one-to-one customer experience
Here is a quick interview with our Data and AI Consultant, Jasmine Caur, to understand why should retailers do away with the one-size-fits-all approach and must travel from segmentation to personalization to improve the effectiveness of their campaigns.
Why should retailers segment their customers?
To optimize marketing spend, product promotions and customer service.
- Customer segmentation helps retailers get a better understanding of their performance. Metrics relating to sales, marketing campaigns, and incentive programs can all be broken down into segments based on the customer’s transactional data. Apart from transactional data, demographics, the lifecycle of the customers and their behavioural attributes make for great data sets when looking at segmenting the customers. With the number of marketing channels available to retailers, segmenting customers has become inevitable – to drive profitable growth.
- As per this customer segmentation study by Mailchimp,
- Segmented campaigns performed markedly better, with an opening rate of 14% higher than non-segmented campaigns.
- Segmented campaigns have a 100% chance of being clicked compared to non-segmented ones.
What kind of data do retailers need for customer segmentation?
It is helpful to think the customer segments in terms of the 5 W’s–and an H (who, what, where, when, why and how).
- ‘Who’ will outline the basic demographics of the customer, including gender, age, income, education level, occupation, and marital status.
- ‘Where’ will give insights into where the customers live, it is more than just circling locations on the map. It provides an understanding of customer concentration and diversity. Geographic data includes rural or urban, Domestic or international, city names, and regions, among others.
- ‘What’ will answer the past, present, and future of the customers. Here, think in terms of transaction history, context and motivation of the purchases, and attitudes and psychographics of the customers.
- Data points for ‘when’ will include the season, day of the week, life-events, and time of the day, in which your customers shop the most.
- ‘How’ to customers interact with the service or product – in-store or online, direct or reseller, and in-person or phone.
What are some methods to segment the customers?
- Compared to a simple threshold or rule-based segmentation, cluster analysis has two significant advantages: Practicality and homogeneity. In the dashboard, we have used two methods of clustering to create segments: RFM (Recency, Frequency, Monetary) and CLARA (Clustering Large Applications).
- RFM groups customers based on their transaction history – how recently, how often, and how much did they buy. To further simplify, Recency (R) can be defined as days since last purchase i.e., how many days ago was their recent purchase – 1 day ago, 14 days ago or 500 days ago.
Frequency (F) is the total number of transactions i.e., how many times has the customer purchased? For example, if someone placed 10 orders over a period, their frequency is 10. Monetary (M) is total money spent, or how much has this customer spent? Again, limit to last two years – or take all the time. Total up the money from all transactions to get the (M) value.
- CLARA is an extension of the k-medoids approach for many objects. It works by clustering a sample from the dataset and then assigns all objects in the data set to these clusters. Here we have considered the demographics and the household income to create groups.
What must retailers do with the segmented Data?
- Fostering brand loyalty is the end goal of all marketing efforts. All the data collected from customer segmentation along with advances in technology and analytics will allow retailers to create much more personalized, relevant, and engaging advertising campaigns across moments, channels, and buying stages.
- As per this 2017 study by The Boston Consulting Group (BCG), “Personalization leaders stand to capture a disproportionate share of category profits while slow movers will lose customers, share, and profits. Over the next five years in three sectors alone—retail, health care, and financial services—personalization will push a revenue shift of some $800 billion to the 15% of companies that get it right”. Personalization Is No Longer A Maybe — It’s A Must-Have.
The underlining idea is to have a 360-degree view of your customers. Right from tracking the interaction they’ve had with the company sales and after-sales teams, and what marketing campaigns they have engaged with, among others – it is all about knowing the customer’s story from beginning to end. Not only will this empower the retailers to deliver the right services at the right time, irrespective of the channel, but also help in personalizing the customer experience.
From data to actionable insights, Motifworks empowers retailers to answer critical questions and take prompt and optimized actions – improving profit growth and customer relationships. Transform your retail business with engaging brand experiences.
To learn more about Motifworks’ Retail Analytics solutions – Click Here