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How to increase CLV & decrease CAC - Valentin Radu
This document provides strategies for increasing Customer Lifetime Value (CLV) and decreasing Customer Acquisition Cost (CAC) in e-commerce through customer segmentation and behavioral analysis, specifically using RFM (Recency, Frequency, Monetary) segmentation. It emphasizes the importance of understanding customer behavior to tailor marketing efforts effectively and the need for a customer-centric approach within organizations. Additionally, it discusses monitoring customer experiences and making data-driven decisions to optimize acquisition and retention efforts.
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Introduction to increasing Customer Lifetime Value (CLV) and decreasing Customer Acquisition Cost (CAC) with foundational growth eCommerce strategies.
Introduction to increasing Customer Lifetime Value (CLV) and decreasing Customer Acquisition Cost (CAC) with foundational growth eCommerce strategies.
Insight on rising customer acquisition costs and the importance of targeting and conversion strategies to improve customer retention.
Highlighting the significance of customer segmentation in enhancing CLV and reducing CAC, introducing RFM segmentation techniques.
Detailed description of RFM analysis groups, illustrating characteristics and performance of different customer segments.
Actionable strategies aimed at nurturing key customer segments to optimize CLV by improving their experience and engagement.
Analysis of revenue and CLV by RFM group, focusing on the essential methods to enhance CLV and reduce CAC.
Explaining the transition from product-centric to customer-centric strategies to better monitor customer behavior and satisfaction.
Identifying critical metrics such as CAC, NPS, CLV, and retention to measure and manage customer relationships effectively.
Utilizing data to assess chances of customers placing future orders and emphasizing the impact of time on ordering behavior.
The importance of integrating qualitative feedback to enhance customer understanding and improve acquisition and retention approaches.
Links to additional resources for expanding knowledge in customer value optimization and appreciation for the audience.
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How to increase CLV & decrease CAC - Valentin Radu
- 1. How to increaseCLV & decrease CAC Valentin Radu | 8th of December 2021
- 2. 01 02 03 04 05 The eCommerce GrowthFormula What affects the CLV Customer Segmentation How to Improve CLV The CVO Impact
- 3. There Are OnlyTwo Ways To Grow Any Business A. Acquire more customers B. Get each customer to buy from you more & more often
- 4. The common growtheCommerce formula
- 6. The actual growtheCommerce formula
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- 8. *Source: Wordstream stateof Facebook Advertising, eMarketer and Statista Since 2013, Facebook CPC has grown 8 times, while retail eCommerce sales worldwide have increased by 158% Retail eCommerce Sales worldwide 2013 -2021 (158% growth) Average Facebook CPC 2013 - 2021 (800% growth) More customers: Traffic
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- 10. Acquisition Conversion Retention ++ Customer Value Optimization Customer research > Better targeting Better creatives Better ROAS Customer research > Better UX & LPs More relevant messaging Better conversion rate Customer research > Better Onboarding Better Remarketing Better customer retention
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- 13. Initial Symptoms +95% <20% RevenueCustomer Retention -20% <40 YoY CLV NPS
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- 15. "For many events,roughly 80% of the effects come from 20% of the causes" True in eCommerce, as well. Vilfredo Pareto
- 16. Not all thecustomers are created equal. Some are better than the others. The best ones = Ideal Customer Profile (ICP)
- 17. 1 ICP generatesmargin as much as 376 low-value customers. It’s not fair smart to treat everyone the same.
- 18. R F M Howto improve CLV & decrease CAC using RFM Segmentation
- 19. RFM Analysis 30% After 30%of the revenue is generated by returning customers, you have to do RFM segmentation
- 20. RFM is anacronym for: RFM Customer Segmentation RFM segmentation is a method to identify the most important type of customers by grouping them according scores to their recency, frequency & monetary values. That allows companies to target specific clusters of customers with more relevant for their particular behavior – and thus generating higher rates of response, increased loyalty and better customer lifetime value. “How recently did the customer purchase?” “How often do they purchase?” “How much do they spend?” ECENCY REQUENCY ONETARY R F M
- 21. RFM Groups Soulmates Your mostfrequent buyers, have placed the highest number of orders and of the highest value. Ex-Lovers They used to be True lovers, but have abandoned buying from your website. Lover Active, have placed a good amount of orders or significant value. Potential lover Potential to become active customers, have placed more orders than Flirting. Flirting Have placed more than 3 orders of high value. Passionate new ones Have placed their second order, with a high monetary value. Platonic friend Active, have placed a moderate amount of orders or moderate value. About to dump you Rather inactive; have placed last order more than half a year ago. Fresh apprentice Fresh ones, have just placed their first order. Breakup Inactive & low value spenders.
- 22. Depending on theclient base one can define fewer or more of the RFM groups exemplified above. For small client bases there’s no need to have a large number of groups. The idea is to have manageable chunks of people that share a particular behaviour in relation to your company. Soulmates These customers bought: > Most recently > Most often > Highest monetary values R F M 5 = 5 = 5 = Share of Customers: 3,21% Share of Revenue: 12,42%
- 23. Total lifetime ofthe shop 5.6% of the customers 24.6% of the revenue Last Month 20.2% of the customers 19.9% of the revenue
- 24. RFM Analysis RFM analysisreveals data anomalies that allows eCommerce managers to understand which are the most important groups of customers when they balance the customer acquisition cost with the margin they generate. “Soulmates” customer group is one of the smallest, but the most profitable.
- 25. Last month Lifetime Next steps 1.Monitor their customer experience in real-time 2. Treat their objections in real-time 3. Research the ICP and build look-a-like audiences Main Goal Keep them happy & acquire more like them 1.7% 10.1% Customers Revenue 20.1% Customers Revenue 19.1%
- 26. Last month Lifetime 1.6%1.8% Customers Revenue 18.4% Customers Revenue 24% Next steps 1. Surprise & Delight them 2. Run Cohort A/B testing to identify how to onboard the next ones better 3. Run tailor-made campaigns Main Goal Persuade them to place the2nd order
- 27. Next steps 1. Treattheir objections in real-time 2. Run tailor-made campaigns 3. Acquire more like them Main Goal Transform them in Soulmates Last month Lifetime 5% 25% Customers Revenue 12% Customers Revenue 14%
- 28. Ex-Lovers These customers bought: >Many times > A long time ago > High monetary values R F M 1 = = = 5 5 Depending on the client base one can define fewer or more of the RFM groups exemplified above. For small client bases there’s no need to have a large number of groups. The idea is to have manageable chunks of people that share a particular behaviour in relation to your company.
- 29. Last month Lifetime 20%29% Customers Revenue 0% Customers Revenue 0% Next steps 1. Find what stopped them from buying 2. Treat their objections 3. Tailor-made campaigns Main Goal Re-engage them
- 30. Don Juan These customersbought: > A long time ago > Only once > Big monetary values R F M 1 = = = 1 5 Depending on the client base one can define fewer or more of the RFM groups exemplified above. For small client bases there’s no need to have a large number of groups. The idea is to have manageable chunks of people that share a particular behaviour in relation to your website.
- 31. It is crucialto monitor the user experience and the customer experience
- 32. Next steps 1. Findwhat stopped them from buying 2. Treat their objections 3. Tailor-made campaigns Main Goal Re-engage them Last month Lifetime 20% 29% Customers Revenue 0% Customers Revenue 0%
- 33. Revenue by segment Revenueby RFM Group
- 34. CLV by RFMGroup
- 35. How to improve CLV &decrease CAC
- 36. 1. Change thecompany mentality
- 37. Customer-centric 2 Types ofcompanies ● They realize that the main driver of demand is customer behavior. ● They know that customer behavior can be monitored and influenced by analyzing the data. ● Success for them means CX, CLV, Customer retention ● Their departments are all orchestrating a fluent customer journey ● Have a unique source of truth around their customers. ● They segment, monitor, understand and nurture their customers with the latest technologies. ● Think that the demand just happens out of the blue ● Communicate mainly features, price or discounts. ● Define success by looking only at things like traffic, CPC, or revenue. ● Their departments are silos that run separately and treat customers without understanding the previous and the next touchpoint in their customer journey. ● Vulnerable to competition & market changes Product-centric
- 38. 2. Monitor whatmatters
- 39. CAC Customer AcquisitionCost NPS Net Promoter Score CLV Customer Lifetime Value M Margin RR Customer Retention DBT Days Between Transactions CLV Customer Lifetime Value
- 40. Chances to placethe next order Source: Omniconvert Reveal, aggregated data from 2231 stores https://www.omniconvert.com/customer-lifetime-value-ecommerce-benchmark/
- 41. Chances to placethe next order Source: Omniconvert Reveal, aggregated data from 151 stores
- 42. 1 2 2 3 34 order order order order order order Chances to place the next order 23.6% 38.1% 47.2% 61% higher 101% higher!!! Source: Omniconvert Reveal, aggregated data from 151 stores
- 43. 1 order After 24 days... Chancesto place the next order 80% Source: Omniconvert Reveal, aggregated data from 151 stores After 193 days... chances 20% chances
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- 45. Add the customervoice in the mix to correlate the customer feedback with the quantitative data The Qualitative research will reveal customer groups’ reasons to buy and the barriers in relation to Products and Services. These will be translated into insights that will help define the Ideal Customer Profile.
- 46. Soulmates Lovers Ex Lovers Flirting About todump Breakup Fresh Platonic Friends Don Juans # of recipients 3334 (3.21%) 8486 (8.17%) 3722 (3.58%) 571 (0.55%) 25,728 (24.78%) 25,761 (24.81%) 807 (0.78%) 2011 (1.94%) 103 (0.10%) NPS Demographics Reasons won Main Barriers Reasons lost JTBD
- 47. Qualitative research Insights Products issues Quality Features Price Brand Servicesissues Delivery time Delivery cost Client Service Return policy JTBD data Struggling moments Jobs Triggers Forces of progress
- 48. 4. Improve CustomerAcquisition > Conversion > Retention
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