Every marketer optimizes for CAC. But what about marginal CAC for your most valuable segment?
Understanding who’s your most valuable customer is at the core of customer equity. In B2B, this is situated around understanding the ICP, the Ideal Customer Profile. For B2C, this is often different as there are more SKUs, and margins might differ per SKU. However, you would rather acquire a customer that can generate profit in years to come than acquire a customer that will churn after an initial purchase. Understanding purchase behavior and forecasting future CLTV (fCLTV) is well documented. Enriching it with customer demographics and attributes will help consumer-focused companies better understand who their ideal customer is. Through this, it can support marketing organizations by enhancing customer targeting and improving messaging.
There is plenty of great literature on the inner workings of customer equity, including The Age of Customer Equity, Customer Centricity, Theta’s Blog, and The Customer Base Audit.
Understanding Customer Equity & Use Cases
✖️ (Future) Customer Lifetime Value – Customer Acquisition Cost = Customer Equity
- Understanding marketing channels: where are our most valuable customers coming from?
- Understanding purchase behavior: what purchases & SKUs drive long-term customer equity? → What SKUs or product categories are the most profitable? → What customer purchases & satisfaction will lead to long-term retention?
Enhanced customer insights through customer equity
Through retrieving additional customer attributes, we gained more insights into their household size and the presence of children or pets. This helps drive valuable context into the customer’s motivations and needs.
Examples:
- If a prospective customer has a vehicle capable of towing an RV, it provides valuable context in the search process as we can filter out Travel Trailers or Fifth Wheels that require significant towing capacity.
- If the customer is a pet owner, they are more likely to rent an RV than choose other travel alternatives, making them a more useful acquisition target.
Collecting Insights with Data Enrichment Providers
Automating the process to enrich customers can be done directly through the APIs & services that are provided by some of the popular vendors in the space, both for B2B and B2C. Pick the one that makes the most sense for your business and can provide helpful attributes through enrichment.
Popular data enrichment providers: AccuData, Response Marketing Group, Axciom, Epsilon, Experian, RocketReach, Apollo, and FullContact.
This data helped provide useful insights. For example, RV travel is more geared toward traveling with your pet than alternatives. Learning that pet owners’ retention outperforms averages by >20% helps drive new customer acquisition strategies and targeting/messaging.
What data could be useful? The device, location, household size, household income, dwelling type, car type, interests, mortgage, credit status, donations (and towards what causes), pets in the household, you name it. It can be provided by most vendors. Use it respectfully & follow ethical standards.
New Opportunities Made Possible
Contextual data → better targeting → efficient CAC
The more you understand a customer’s attributes, the more you can leverage them across the two most important areas to gain efficiency and build new innovative ways to engage customers.
Targeting & Messaging
- Sync customer attributes to your ESP to power segmentation & target customer messaging.
- Create customer lists with common attributes for ad targeting.
- Enhance customer insights for customers X via data clean rooms.
New Customer Acquisition
- Increase bids based on high-value customers with specific customer attributes.
- Sync pet owners to Facebook Ads to build look-a-like audiences to target similar customers.
The Inner Workings: Syncing Customer Insights via MarTech
After initiating a relationship with your preferred data enrichment vendor and collecting the data, you want to make it actionable and enhance your marketing technology stack to have access to these attributes. This is where reverse ETL comes in; at RVshare, we use Census to support this.
Syncing Customer Data into Iterable (ESP) via Census
Our enhanced customer data lives in Google BigQuery, outside of our core infrastructure, to avoid any production-level issues for marketing use cases. The data is an easy flat table consisting of a customer identifier (user-id or email) + columns for customer attributes. This way, we can connect it to transactions for customer equity insights. In the following example we sync this data back into Iterable.
Creating a Sync in Census
- Set up Google BigQuery (or your preferred warehouse) as a Source.
- Set up Iterable as a Destination.
- Set up a Sync with your specific, enriched, segment and connect BigQuery to your Iterable User via its user identifier.
