RFM segmentation is a powerful tool to segment your customer base according to the recence, frequency and purchase amount.

As part of reactivation of passive customers, it is one of the most used methods to create one or more segments of passive customers. Each segment is then the subject of a personalized reactivation scenario.

For example, we can imagine the following approach:

• Passive “small customers”> simple reactivation scenario with 2 email messages (popular products, promo code, ..)
• Passive “big customers”> Multichannel reactivation scenario with email sending, then Retargeting Google / Facebook Ads, then mail or outgoing telephone call.

Thanks to Octolis, you can easily set up a very flexible RFM segmentation, and synchronize it with your different CRM / Marketing tools.

How RFM segmentation works

RFM segmentation classifies customers according to their individual buying behavior.
Each contact is scored based on 3 criteria:

• R = Recency of last purchase.
• F = Frequency of purchases.
• M = Cumulative amount of purchases.

For each criterion, the contact has a relative score ranging from 1 (low) to 6 (high).
For example, if a contact has R = 1, it means that he or she is part of the 1/6 of the database of customers with the oldest last purchase date.
Next, we combine the F and M ratings into “FxM” to get a two-dimensional rating on which segments are based.
For example, we can define the segment “Best customers become passive” with R IN {1,2} and FxM IN {5,6}.

In theory, with a 2-dimensional scoring, having 6 potential values each, you can build up to 6 x 6 = 36 segments. But in general, there is no point in having more than 10 segments.

Repeat customers may represent a significant part of your revenues. To generate more revenues from your repeat customers, you need follow-up with them at the relevant timing, when a message may trigger a new purchase.
This imply to segment your repeat buyers according to their progression in the purchasing journey, to know if the buyer is ahead or late on his usual purchase journey. For example, if a customer buys on average every 6 months, and he has not bought for 8 months, he is late compared to his usual cycle, and it may be a good timing to follow-up with him.

With Octolis, you will have a new column for each customer indicating his position in the usual purchase. Customers are gathered in several segments: recent purchase, soon reached, late, very late, and inactive.

This segmentation could be broken down by product categories, which is very relevant when there are some categories with lot of produits purchased on regular basis.

What are the main use cases?

• Stimulate the re-purchase of “late” customers by setting up specific triggers or reactivation campaigns.
• Implement more aggressive anti-churn actions across multiple channels (outbound phone call, postal mail, carrier pigeon, ..) for significantly late and inactive customers.
• Analyze the share of early and late customers by product category, customer cohort, etc.

Marketing pressure is measured through the number of messages sent to your contacts over a given period. With increasingly multichannel marketing, it is obviously more and more difficult to measure and adjust the level of marketing pressure.

With Octolis, it becomes much simpler.
For each contact, you will have new columns in your marketing tools to know:

• How many messages he received: emails, sms, letters, etc.
• How many messages have obtained a return: opening, click, response, etc.
• To what extent is the contact is “over-pressure” or “under pressure” compared to the others in order to adjust the level of future pressure.
• To what extent contact reacts well to an increase in marketing pressure. In other words, if I continue to send him messages, do I have a chance to generate more feedback, or on the contrary to generate a unsubscription.

We are talking about promophile customers to characterize customers who mainly buy products with commercial discounts. It may be very useful to identify promophiles in order to target them in certain promotional campaigns, or on the contrary to exclude them.

With Octolis, you will have an updated promophilia score for each customer for each purchase.

• This score is based on the purchase propensity made with a discount, in value and number of purchases.
• This score will be synchronized in real time with your emailing/marketing automation tool.

You can personalize this score easily. For example, you can adjust the weight of the criteria such as the repair volume on the cumulative CA or the number of purchases with discount, or to calculate this score only for customers who have made more than 3 purchases.

The objective is to know for each customer which products are most likely to generate a new order. The product recommendation takes into account several criteria:

• What are the products already bought by this customer?
• What are the (categories of) products purchased by other customers who have purchased these same products?
• What are the products that have been visited on the website without being purchased?

With Octolis, you can activate an easy -to -customize product recommendation score.
For each client, you will get new columns with:

• The list of IDS Products to be recommended as a priority,
• The list of product categories to be recommended as a priority,
• Images, names, product description to recommend.

These new columns will be synchronized in real time in your emailing / marketing automation tool so that you can use them as personalization variables in your emails.

What are the main use cases?

Web personalization: Push recommended products at different stages of the web user journey, in a dynamic block of certain pages, or in a popup.

Any channel: Most touch points in the customer journey can be used to up-sell or cross-sell to your existing customers (outbound phone calls, postal mail promotion, etc.)

The reactivation of passive customers is a big lever to generate new sales. The email follow-up is not enough. To reactivate a large share of your passive customers, you must use several channels, and adjust your efforts according to the potential of each customer.

This means segment your customers according to their purchase history (ideally with RFM segmentation) and put a greater effort to reactivate your “big” passive customers. Concretely, this means to follow-up large customers 5 times, and only 2 times the smaller customers, but also call and/or send a letter to large customers, and only follow-up emails to smaller ones, etc.

With Octolis, you can easily orchestrate multichannel passive customers reactivation.

• Create a segment to identify the “big” passive customers,
• Add a priorization score,
• Synchronize the segment in real time to different tools.

If you are considering costly reactivation levers (telephone call, mail, etc.) for large passive customers, prioritization becomes essential. You have to easily choose the top x customers to be recalled as a priority.
In my segment of large passive customers, I will add a score based on their cumulative CA x number of purchases to classify them.

Once the score is added, you can synchronize this segment with the tool used by people who will recall. It can be Google Spreadsheet, Salesforce, Zendesk, etc.