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Client A:             

A large U.S newspaper was seeking to find new ways of generating additional revenue from its home subscription line of business.


The Approach:

After some careful thought and deliberation with the client, it was determined that the most effective approach to undertake to meet this objective would be to focus solely on analyzing and developing new, alternative, creative strategies strictly geared towards new and existing customers. Improving the operational efficiency and returns of “Prospecting” initiatives was deemed as important, however, secondary given the level of difficulty in achieving the desired ROI, cost and operational challenges and restrictions that existed.

Thus, having removed the possibility of increasing sales volume from the equation, our focus was then on developing customer retention and market based re-pricing strategies. In effect, our goal was to determine which customers could possibly bear a rate chain change and / or re-pricing without risk of attrition? More specifically, multiple algorithms were used to predict price sensitivity measures and customer retention across numerous customer segments: (1) existing longer term customers (2) new customers who had recently come onboard through a promotional offer.


Key Learning & Recommendations:

Having generated price sensitivity measures and attrition likelihood rankings across the customer base along with having performed extensive testing, it was determined that “pricing” had indeed minimal effects on future attrition likelihood and therefore, the recommendation was to target the “right” customers with adjustments and to also move them up to a longer term rate, quicker, rather than through numerous discounted rates. Increased revenues would be dictated by the ability to initially place and eventually move the customer into the appropriate rate chain and pricing structure.

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​​​Client B:

A large telecommunications company was seeking to increase its cross-sell ratio for its cable division by applying more effective targeting methodologies. In addition, they were also seeking to understand the dynamics of customer attrition and whether or not this behavior could be predicted and possibly curtailed.


The Approach:

In light of the fact that SAI’s core strength lies in its ability to design and implement new, alternative analytical strategies and methodologies used for enhancing acquisition, cross-sell / up-sell and retention initiatives, this request was deemed the perfect opportunity for us to showcase our analytical capabilities.

Given the number of products available from this division, numerous product specific predictive algorithms were designed and implemented to meet this given objective. In simple terms, SAI provided the client with a file containing a list of customers deemed most “responsive” to whatever product the client was attempting to offer. This information was further passed on to their marketing and call centre teams to support ongoing and future campaigns.

In addition, much like the design of algorithms used for targeting purposes, algorithms can also be designed to predict customer attrition. Incorporating profitability information along with reason codes will allow you to focus your attention on your most valuable customers and also enhance your ability to prevent them from possibly leaving.


Key Learning & Recommendations:

Be as proactive as possible!! Learn, test and modify existing solutions going forward based on the results of your campaigns.

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​​Client C:

 

A large international software company was seeking to acquire new business customers more effectively and at a much lower cost per acquisition. In simple terms, they were seeking to improve their ROI from prospecting campaigns.


The Approach:

Unsatisfied with their current results and cost per acquisition, it was time for them to test and implement new, alternative, more effective targeting methodologies. No longer would negative ROI be an acceptable rate of return. In order to improve returns as best possible, SAI therefore recommended the design and development of a “response” based predictive algorithm specifically designed to optimize returns.

This model, more predictive in its design, would be developed using the results of prior campaigns. This would allow them to substantially refine their targeting efforts. Only the most responsive prospects would be contacted, substantially reducing costs leading to increased ROI. Prospects would be rank ordered in terms of their likelihood to “purchase” and then selected for calling. In the end, the objective is to also further operationalize the process so that systematic use of these algorithms is easy and seamless.


Key Learning & Recommendations:

In order to increase your likelihood of success, one must make sure that the design of the algorithm, and more specifically sampling, is done correctly otherwise future applications may be in vain. Allowing the campaign to also run its full course until completion is also critical. Other issues of concern may be file fatigue or saturation and lastly, one must set-up test and control cells for validation purposes.

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​​Client D:

 

A large automaker was seeking to establish a relationship or connection with prospects who in the past, may have shown or expressed an interest in possibly leasing or purchasing one of their vehicles. The challenge was, who to target and how to do it as effectively as possible at an acceptable cost.


The Approach:

Using all available data sources within the industry along with recent “purchasers” and “in-the-market” data, predictive algorithms can be designed and implemented to identify and rank order potential prospects in terms of their likelihood to “lease or purchase” an automobile in the near future.

SAI therefore designed and developed such an algorithm specifically for this purpose. This initiative would allow and provide the automaker with a strategic way of leveraging the information contained dormant within their prospect databases. More importantly, however, was that it would allow them to substantially refine their targeting efforts and to also establish that key contact which could lead to a future lease or purchase. Only the most responsive prospects were selected for contact, substantially reducing costs.


Key Learning & Recommendations:

The sooner one attempts to establish a relationship or make contact with a potential buyer, the better. It’s all about engaging the customer or prospect. Generally speaking, it’s simple to understand that the stronger the relationship and the further back that initial contact goes, the more likely a prospect is to lease or purchase one of your vehicles. That likelihood also increases if the potential buyer also requests information on their own. The opportunity to engage with a prospect must be seen as the “seed” to bringing onboard a potential future customer.

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