Information Advantage

Recommendation 4: Comprehensive Valuation of Marketing Campaigns

by Bill Abbott on July 26, 2010 by Bill Abbott and Kemal Karakaya

In the last post of our four-part series on customer retention strategies, I would like to look at the impact of marketing campaigns on churn. Marketing or sales campaigns can impact churn, regardless of their primary goals. For example, contract renewal campaigns can have the unintended effect of reminding forgetful wireless customers that their contracts have already expired, and that they are free to explore the marketplace for better deals. Unfortunately, companies rarely remember to consider unintended churn when evaluating financial impacts of marketing campaigns—which often leads to poor decisions. Similarly, excessive efforts by companies to promote up-sells (such as credit card payment protection services) can have the inadvertent effect of irritating some customers and causing them to cancel existing services altogether.

An effective approach will include churn impact in the valuation of any campaign. This will help decision makers evaluate the list of campaigns on a set of standard financial metrics and roll-out the winners. Unfortunately, in my experience, this simple solution hits a road block when the acquisition and retention functions are separated across an organization. Campaigns managed by marketing or customer acquisition groups do not typically account for churn. By contrast, campaigns run by retention groups will be more likely to have an incentive to address churn. For example, call center representatives might be asked to substitute low-end packages with high-end offers at no new cost, or to decrease the price of current services in order to combat competitive pricing pressures.

Marketing and customer acquisition efforts comprise by far the most common type of campaigns, so organizations must do a better job of considering churn in these instances. Marketing and sales departments should work with support organizations to bolster the NPV models of their campaigns by gathering customer data on actual churn outcomes. Depending on the availability and quality of data, these departments should also consider supplementing the analysis with primary or secondary research.

The credit card industry provides one of the best examples of this integrated approach. Most of the best-in-class credit card issuers are diligent about managing their churn risks, and they achieve financial valuations that estimate and measure churn impact for all their campaigns—valuations that include added exposure of a new customer and the incremental credit line. Only campaigns that pass a specific level of rigorous scrutiny are introduced to the market. This industry example illustrates a key point: Companies will reduce churn and increase the marketing value if they can identify and refine, or eliminate, campaigns in which the churn cost negates or exceeds any new value created from adding or retaining customers.

Conclusion

It is necessary to develop a comprehensive approach to customer retention and churn management, considering not only their external drivers, but also internal factors that may impede an effective response. By adhering to our specific guidelines and principles, companies can build a strategic foundation for successfully managing churn and increase their retention rates consistently over the long term.

Keep in mind there is no silver bullet for churn reduction. Guidelines, tactics, and strategies will vary for each company; the only sure-fire approach for reducing churn is to develop a custom, comprehensive strategy and to execute that strategy through quality program management and coordination across the organization. Successful execution will routinely pay significant dividends, as low churn rates can vault a company to economic health and industry leadership in terms of profitability and brand equity.

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Market and Agent Performance Toolset for Insurance Companies

by Nidhi Rustagi on July 26, 2010 by Nidhi Rustagi, Amaresh Tripathy, Mudit Mathur, Anand Rao and Sundeep Thakkar

Market and Agent Performance Toolset for Insurance Companies

Some time back our Partner Anand S. Rao and Jamie Yoder posted a story around the future of commercial insurance segments and how the dynamics of small commercial segment is playing out differently from that of mid-market commercial segments.

To put it succinctly, the pitch around small commercial segment is that of efficiency and effectiveness which is about getting more policies through automated/semi-automated underwriting while focusing the underwriter’s efforts on high-value cases. As one moves to mid-market and high-end commercial segments the story is around promising and delivering the right ‘value proposition’ with high-touch, tailored offerings. Being able to identify the right markets at a granular level (i.e. zip codes) with the right customer segments (i.e., business size, underwriter appetite) and the right agents to reach them becomes critical.

One of the key challenges is to identify the high-value agents as well as reduce the cost-to-serve. Add to this the complexity that more and more customers understand the basic insurance products (e.g. auto, term life) and do not rely on agent expertise as much as they used to do in the past. The customers are also empowered by online channels where they can get comparative quotes in a matter of minutes and can avoid agent interactions.

These trends have put a lot of pressure on insurance companies which continue to see reduced returns from their agent channel.

At Diamond, we have been helping our Insurance clients to adjust their agent strategies for a long time, and with the recent launch of our ‘agent performance’ toolset we can not only significantly reduce the analysis time,  but also showcase the results with simple yet visually-appealing result sets and gain quicker buy-in of the recommended changes. Some of the typical questions that executives struggle to answer in regard to their agent force:

  • Which markets have the highest headroom for growth?
  • How profitable are existing agents?
  • How to improve agent profitability?
  • How can we identify high performing agents

We deployed the agent profitability toolset for one of our insurance clients, which helped the client identify ~55% agents that could not meet the 15% hurdle rate (ROI). With the visual interface we were able to dive deep into agent locations, prevalent market demand and current profitability.

We believe that DemandEstimator’s Agent Profitability Toolset goes a long way in helping executives take strategic and tactical decisions in order to improve overall agent performance and impact business performance.

View the demo here and let us have your feedback

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Recommendation 3: Enforcing Channel Performance Standards

July 19, 2010

In the third part of my four-part series on customer retention strategies, I would like to focus on the importance of channel management. Service providers in many industries find it beneficial to employ a combination of in-house and third-party channels to acquire and serve customers. For example, insurance providers use a mix of dedicated and [...]

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Recommendation 2: Predictive Modeling vs. Business Rules

July 12, 2010

In the first post of this four-part series, I talked about how to take predictive modeling to the next level by making it more targeted and hence driving more profitable retention campaigns for organizations. The next question I would like to discuss is if there are instances when the value of predictive models might be [...]

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Analytics to the Rescue: How to Retain your Profitable Customers?

July 6, 2010

Analytics to the Rescue: How to Retain your Profitable Customers? In December 2006, my colleagues Bill Abbott, Franziska Gomez and I published “Curing Customer Churn,” in which we identified the challenges of churn management and outlined an approach for developing a better understanding of churn drivers. We recommended using a combination of careful call monitoring, [...]

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Datawarehouse Selection – When to Implement a Database Appliance Over a Traditional Database, and Vice Versa

June 28, 2010

Part 1 Of 4 – Introduction While the ‘age old’ data warehouse requirements of speed, quality and accuracy have not changed, database hardware and software technologies are becoming more efficient, more intelligent, and can automate many tasks previously undertaken manually by DBAs. The last decade has seen companies such as Teradata, Netezza, and HP (with [...]

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Using Analytics and Visualization to Measure Performance and Identify Future Opportunities

June 9, 2010

Striving for information advantage in today’s world, companies spend non-trivial amounts of money, time and resources to understand the current state of their firm and the potential demand for their product. Recently, Diamond helped a leading Latin American Insurance provider assess the performance of its cell phone insurance product and identify potential high demand areas [...]

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Predictive Analytics: 8 Things to Keep in Mind (Part 7)

June 2, 2010

Theme 7: Prototype, Pilot, Scale Edison did not invent the light bulb. He took a working concept and developed hundreds of prototypes rapidly, tested them and along the way figured out improvements that were required to scale his invention for commercial use. Julian Trubin writes about the prototyping process: In 1879 Edison obtained an improved [...]

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Demystifying Real time Data Warehouses – Part 2

May 19, 2010

In my previous blog, I had explored the definitional side of ‘real-time datawarehousing’ and talked about few examples of how companies can yield tangible business benefits by using these technologies. Now it’s time to talk about the components of this technology set and the ballpark costs for acquiring and implementing it. At Diamond, we seldom [...]

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Value-Based Master Data Management

May 18, 2010

In its May issue that just published, Consumer Goods Technology has a great article on the global master data management (MDM) program Kraft Foods is executing with Diamond’s help. Talking with Anbu Mani, a colleague here at Diamond, two things stand out in the piece.  First, Kraft Foods had a clear set of business problems [...]

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