One of the primary tools employed by Blend was Reveal’s RFM (Recency, Frequency, Monetary) analysis, which allowed for effective customer segmentation based on purchase history and engagement levels. RFM analysis is a technique used to categorise customers into segments based on three key factors:
- Recency: The time since the customer's last purchase. Recent customers are often more engaged and likely to make repeat purchases.
- Frequency: The number of purchases made by the customer over a specific period. Customers who make frequent purchases are indicative of higher engagement and loyalty.
- Monetary Value: The total amount of money spent by the customer on purchases. Customers with higher monetary value contribute more to the business's revenue.
Through RFM analysis, several key findings emerged.
Firstly, a clear understanding of the demographics of power customers was established, helping identify the characteristics and preferences of the most valuable customer segment.
Additionally, the analysis highlighted specific products that showed high stickiness and others that were deemed toxic, allowing for appropriate promotion or discontinuation strategies. Furthermore, purchase frequencies were identified, enabling the optimisation of subscription frequencies and retention marketing efforts tailored to each customer’s journey.
To capitalise on these insights and elevate customers to the highest RFM level, known as "Lovers" who are highly valuable, loyal, and premium-paying customers, Blend devised effective strategies:
- The team aimed to attract lookalike power customers, targeting individuals who shared similar characteristics and behaviours with existing high-value customers.
- By identifying the sticky products, Blend promoted them to drive increased engagement and loyalty. Simultaneously, toxic products were either demoted or discontinued to prevent negative customer experiences and mitigate any adverse effects.
- Subscription frequencies were timed and aligned with each customer's likely purchase frequency, ensuring a seamless and optimised experience throughout their customer journey.
That’s not all though.
Through the integration of Omniconvert’s Reveal and Klaviyo, Blend successfully implemented a targeted email marketing strategy that addressed each customer's specific needs and behaviour based on their RFM level.
By using the RFM data, Blend could identify customers who had a low purchase frequency and design personalised email campaigns in Klaviyo to re-engage them and encourage more frequent purchases. Customers who had not made a purchase in a while could be targeted with tailored email offers, highlighting new products, subscription messaging, exclusive discounts, or personalised recommendations based on their previous purchases. By delivering relevant and timely messaging through email, Blend aimed to increase customer engagement, drive repeat purchases, and ultimately move customers to the highest RFM level.
The proof is in the pudding, as they say. Through email marketing alone, we were able to increase their Owned Revenue by 56%.
The second tool we utilised for this client's CVO package was conducting NPS (Net Promoter Score) surveys, powered by Omniconvert. NPS surveys are a widely recognised method for assessing customer satisfaction and loyalty. They measure the likelihood of customers recommending a company's products or services to others, using a scale from 0 to 10.
These surveys revealed a lower-than-expected price sensitivity among customers, emphasised the need for improved customer service speed, highlighted the issue of overstocked inventory, and showcased genuine customer love for our products.
In response, Blend implemented effective solutions, refining product messaging to better communicate value, enhancing customer service tools to improve response times, reducing bulk purchase discounts to avoid overstocking, and aligning subscription options with customers' specific needs.
Additionally, Klaviyo and Omniconvert's integration further enhanced the value by enabling the creation of NPS Survey Request Emails. These emails not only directed customers to provide feedback but also fed the data back into Klaviyo, allowing us to take targeted actions based on customers' NPS scores, providing continuous improvement and an enhanced customer experience.
The third tool employed by Blend was that of Message Mining, which involved analysing customer reviews, testimonials, visitor feedback, customer support interactions, and competitors. This process allowed for a deeper understanding of customer pain points, key benefits, and common objections.
Based on the message mining insights, Blend devised effective strategies to address these findings.
- Product page copy was rewritten using the problem-agitate-solution (PAS) framework, emphasising how the products solved customers' pain points
- Detailed FAQs that specifically targeted the most common concerns identified through message mining and customer feedback analysis were developed
- Language levels were adjusted to ensure a more understandable communication style
