Data analytics and customer retention are no strangers to the consumer marketing side of the news media industry, especially publishers with a subscription model. Establishing and monitoring key performance indicators for starts, stops, and churn risk has become par for the course in subscriber retention strategies for publishers.
However, advertising customer retention has often been addressed as a relationship issue. After all, most news media companies close sales through account executives pitching advertising on a one-to-one basis with customers. While the addition of marketing services has made the sales process more complex, it has not changed the underlying need to increase customer loyalty and retention.
Things to keep in mind
Each news media company has a somewhat different advertising and marketing product portfolio. However, one thing is likely the same: Some advertising clients are more transactional, and some are on longer-term contracts with more of a marketing partnership established.
For both types of customers, it’s important to identify data points that can flag potential for churn, as well as ideal contact touch points to encourage retention. Ideally, you want to avoid getting to the point of no return for churn. Analyse your customer life cycles and identify metrics that correlate to higher tendencies to lapse.
However, you can also enlist communication strategies to avoid advertising client churn. Address customer service issues when they happen, and keep communication lines open. Reporting on advertising and marketing campaigns provides a good opportunity to proactively work on client retention, and data is a key component.
- You can demonstrate marketing ROI and your team’s ability to optimise campaigns by showcasing data results.
- You can double check the client’s goals to make sure the planned upcoming campaigns will help them meet their objectives and are optimised toward the appropriate end metrics.
- You can identify opportunities to upsell to solve new problems by applying data to audience targeting.
Avoid second guessing
- Don’t leave signs of potential churn to gut instinct and relationship management: Schibsted, in Oslo, Norway, developed a predictive model and established a churn score, along with a communication model based on those scores. While this was a consumer marketing effort, it provides a good example of applying data analytics alongside a communications process to increase customer retention. Identify ways to tag and signal churn likelihood based on sales transaction data. Then build a communication model that informs both sales and post-sale account management.
- Make your services sticky: Provide additional value through services like data analysis for your advertising clients to help them with better audience targeting and more efficient advertising spend. Sacramento Bee in California, USA, shared some of the many ways it is leveraging the Claritas Urbanicity Model to provide audience insights to retail advertising clients. How can you provide more added value to your advertising and marketing service customers?
- Address second guessing before it’s too late: Gartner (formerly CEB) conducted research on B2B sales and customers, and found B2B customers are “deeply uncertain and stressed.” In a Harvard Business Review report, its analysis went on to share that “second guessing occurs in more than 40% of completed B2B purchases.” CEB said this points to a new sales imperative to make buying easier. Included in this sales imperative is helping your customers avoid second guessing anxiety with a “prescriptive” approach showing you can anticipate and overcome their obstacles.
Develop a data informed strategy
By identifying key metrics tied to customer loyalty and potential churn, you can develop a customer communication strategy informed by data. Actively train around and apply your customer communication strategy to increase customer retention proactively.
And, finally, apply learnings on what tactics work to positively impact your customer retention metrics.