CRM QUICK-win

CRM quick-win

Action list for the A/B test to measure the revenue uplift using the hiper-personalized content on your CRM campaigns.

1. Introduction

Pleasepoint is the AI-based software to personalize interactions and increase the Customer Lifetime Value of all customers. We provide all the tools to personalize in real time and implement a predictive marketing strategy based on quick-wins.

We provide a +57% average revenue uplift and a +53% average orders uplift.

In this document, you will find all the necessary information to prepare the A/B test in 5 days.

The goal of the test is to measure the revenue uplift and the orders uplift by comparing the conversion between the current CRM strategy with the hyper-personalized content on-top campaigns and one-to-one product recommendations.

There are two main use cases two test: the on-top campaigns and the one-to-one recommendation.

On-top campaigns uplift

These are the results for this kind of A/B test with 4 on-top campaigns.

A: Control group

B: On-top audience

Uplift results

The hyper-personalized CRM campaigns using the one-to-one engine has delivered these results:

+65k€ revenue uplift with the 4 on-top campaigns.

+ 10,4% revenue uplift compared with the control group.

+ 7,6% revenue uplift compared with the control group.

The higher the interaction with the CRM campaign, the greater the impact on revenue growth.

One-to-one uplift

These are the results for this kind of A/B test with 4 weeks using the one-to-one recommendation in the newsletters.

A: Control group

B: One-to-one audience

Uplift results

The hyper-personalized CRM campaigns using the one-to-one engine has delivered these results:

+102% revenue uplift with the one-to-one personalization.

+ 75% orders uplift compared with the control group.

+ 14% user click uplift compared with the control group.

The higher the interaction with the CRM campaign, the greater the impact on revenue growth.

2. Test A/B: Revenue uplift

The revenue uplift A/B test consists of measuring the results of the hyper-personalized on-top campaigns.

We recommend making two tests:

  1. On-top campaigns: Add some additional hyper-personalized campaigns and get the uplift using a control group audience.

  2. One-to-one recommendation: Personalize one-to-one the product recommendation on your newsletters and get the uplift using a control group.

With the two actions, you are validating the revenue uplift by adding new hyper-personalized campaigns and the revenue uplift with the one-to-one personalization using your newsletters.

Test 1: On-top campaigns

With the on-top campaigns, we will test the revenue uplift by adding relevant communication to your customers.

To create the on-top campaigns we will use the Customer Lifetime Value and the purchase patterns (Buyer-persona module).

We will create 3 customer segments:

  • Not subscribed: These customers will not receive any CRM campaign.

  • Control Group (CG): These customers only will receive the basic newsletter. We recommend using the 10% as the Control Group.

  • On-top audience: These customers will receive some on-top campaigns. Every customer only will receive the relevant content based on lifetime value and purchase patterns.

To get the results we will compare the on-top audience with the control group. In order to validate these results we can compare the on-top audience with the not subscribed and the control group with the not subscribed.

Remember to use specific UTMs for Google Analytics in order to measure the on-top campaigns conversion.

Test 2: One-to-one recommendation

With the one-to-one product recommendation, we will test the revenue uplift by hyper-personalizing for every customer the product recommendation.

To hyper-personalize the product recommendation we will use the one-to-one module.

We will create 3 customer segments:

  • Not subscribed: These customers will not receive any CRM campaign.

  • Control Group (CG): These customers only will receive a manual product selection. We recommend using the 50% as the Control Group.

  • One-to-one audience: These customers will receive a one-to-one product recommendation.

To get the results we will compare the on-top audience with the control group. In order to validate these results we can compare the on-top audience with the not subscribed and the control group with the not subscribed.

Remember to use specific UTMs for Google Analytics in order to measure the one-to-one conversion.

3. Roadmap

We have planned the task in order to prepare for the A/B test within 5 days. These are the steps that we will follow.

  • Day 1: Data extraction.

    1. Extract all the historic data (CSV files) from your eCommerce (or ERP). Follow the Data extraction documentation.

  • Day 2: Import data.

    1. CSV files validation before being imported.

    2. Import the CSV files into Pleasepoint. Follow the Datalake documentation to import the CSV files.

    3. Google Analytics tracking workshop.

  • Days 3-4: Customer Intelligence.

    1. Customer Intelligence workshop.

    2. Customer enrichment (CLV and buyer-persona).

    3. One-to-one dynamic template.

  • Day 5: Start the test.

    1. Calendar campaigns workshop.

    2. Start the A/B test.