Challenge
An e-commerce company is struggling with low conversion rates and difficulty identifying its most valuable customers.
Traditional methods of customer segmentation were insufficient - they did not take into account the full picture of buying behavior.
To better understand its customers and more effectively tailor marketing campaigns to them, the company used RFM reports available in iPresso.
Action
- Implement RFM analytics in iPresso.
The company integrated purchasing data from its e-commerce platform into the iPresso system, enabling RFM analysis.
RFM is a method of segmenting customers, evaluating them according to 3 criteria: how recently they have made a purchase, how often they buy, how much they spend. - Segmentation of customer base according to RFM analysis.
Based on RFM analysis - easily clickable in iPresso - the store's customers are divided into different segments, such as:- Top customers (high value in all 3 criteria)
- New customers (high Recency value, low Frequency and Monetary)
- Potential loyalty customers (high Frequency and Monetary, medium Recency)
- Customers to be recovered (high Frequency and Monetary in the past, low Recency).
- Personalized marketing campaigns.
Based on the above segments, the store created personalized marketing campaigns for different customer groups. Of course, all campaigns were automated.- Top customers: exclusive offers, loyalty programs, priority access to new products.
- New customers: welcome offers with discounts, shopping guides.
- Potential loyal customers: special promotions, incentives for more frequent purchases.
- Customers to regain: reactivation campaigns with attractive offers.
- Testing, campaign optimization.
The store conducted A/B tests available from iPresso to test the effectiveness of different communication strategies for specific segments.
Based on the test results, campaigns were optimized to maximize their effectiveness. - Performance tracking and reporting.
iPresso provided detailed reports on the performance of marketing campaigns. The company was able to monitor conversion rates, order value and customer retention for each segment, allowing continuous improvement of operations.
Results
Personalized marketing campaigns based on RFM analytics helped increase conversion rates by 25%. Customers were more likely to purchase when they received offers tailored to their behavior and preferences.
RFM segmentation helped target premium offers to the most valuable customers, which contributed to a 15% increase in average order value.
Reactivation campaigns targeting customers for recovery and loyalty programs for top customers increased retention by 20%. Customers were more likely to return and make repeat purchases.
With precise segmentation, the company was able to use its marketing budget more efficiently, targeting campaigns to the most promising segments. This reduced the cost of acquiring new customers and increased the ROI of campaigns.
Personalized offers and communications made customers feel valued and better taken care of, which translated into higher satisfaction levels and positive feedback.
