Case Studies

Win back your clients!

Wondering whether you should invest on winning back customers that you consider “lost”? Is it worth spending money, time and effort trying to re-engage customers with clear signs of disengagement with your brand, such as long term inactive clients or those with decreasing spend? Or should you allocate your scarce resources to attract new customers instead?

Client management strategies applied by ClientIQ, can help you win back highly detached customers, in a way that is 4 times more cost effective compared to attracting new ones!

Case A: Re-engaging Long Term Inactive Customers in Retail Sector

The issue: ClientIQ was called to address and re-engage – in a cost effective way – a portfolio of 200,000 customers that have not transacted with our client for more than 2 years.

The actions: Originally, our marketing team designed and executed a set of pilot campaigns, aiming to identify the offer & communication channel with the maximum revenue and profit potential. Next, our analytics team, analyzed the positive & negative responders’ characteristics, and segmented the inactive portfolio into dinstict customer groups, based on their ability to respond positively to an activation offer. Combining the findings of marketing and analytics team, ClientIQ designed and executed a targeted re-engagement strategy by inactive segment.

The results: By implementing a holistic client management strategy, ClientIQ managed to deliver 3 times higher re-activation rates, 4 times higher net sales per customer and 2 times higher net margin per customer vs. self re-activation metrics, delivering to the business a 12% sales growth

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Case B: Re-engaging Long Term Inactive Customers in the Banking Sector

The issue: ClientIQ was called to reactivate approximately 100,000 customers that have not used our client’s products and services for an average period of 30 months! Trying to win back customers that were disengaged for 2.5 years in a cost effective way was clearly a challenging task.

The actions: Applying a multi segmentation approach on the inactive population, ClientIQ’s Marketing and Analytics teams designed and executed a personalized marketing strategy by segment, addressing to customers with the communication message and channel that was mostly relevant to them.

The results: By implementing a complete client management strategy, ClientIQ managed to deliver unparalleled impact. A population that was adding zero value to the business for almost 3 years, was re-activated at a rate of 27%, generating €6mil incremental sales volume, and €500,000 incremental revenues. And all these at a cost that was 157% lower compared to attracting new customers.

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Case C: Identifying and Addressing Early signs of disengagement

The issue: ClientIQ was called to design and execute a strategy that would minimize spend attrition, so as to protect our client’s sales volume in a very challenging period. The challenge was dual, since our team would first have to effectively identify customers with signs of disengagement and then formulate the appropriate communication language that would convince them to change their spending behavior.

The actions: ClientIQ’s strategy and analytics teams worked together to create an “Engagement Scorecard” correlating internal (i.e. behavioral) with external (i.e. socioeconomic) data for every single customer. Customers with negative engagement index have been selected and offered a truly personalized marketing message designed by our specialized marketing team.

The results: By combining enhanced customer analytics with the appropriate communication message, ClientIQ managed to re-engage 20% of the detached population, generating €2.6mil incremental sales volume and €330,000 incremental revenues, with a cost that was 4 times lower compared to attracting new clients.

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Optimize your company’s offering!

Revisiting your company’s offering is one of the most important aspects of your firm's strategic posture, especially in dynamic environments such as the ones we currently operate. Changes in the macroeconomic or regulatory environment or even changes in consumers’ preferences and values may alter significantly the P&L dynamics of your corporation, while the entrance of new competitors or new technologies may add extra pressures on your financial results.

In ClientIQ – using a holistic client management view – we can help you address the demands of a constantly changing business environment, transforming the need to change from a risk into a competitive advantage that will generate new opportunities for your business.

Case A: Optimizing the pricing strategy

The issue: ClientIQ was called to design an entirely new pricing strategy for its client with the challenging task to meet 3 conflicting requirements at the same time: Set up a price that would not impact customer engagement and would not result in volume loss towards competition, formulate a proposal that would improve profitability despite the environment of diminishing spreads, and respect the local regulatory environment, which allowed small room for flexibility.

The actions: ClientIQ’s strategy team introduced a 360 approach following the “Understand, Measure & Test” rule on every step of the way. Understand through a multi segmentation approach, the price sensitivity of the customer base. Measure the correlation between the price and customer spending, and Test the key components of our pricing proposal directly with the end consumer.

The results: Our results speak for themselves. Using a holistic client management strategy, ClientIQ’s teams managed to improve our customer’s financial performance by €12.6 mln, of which, €6.8 mln being attributed to savings compared to the old pricing and the remaining €5.8 mln being generated by increased customer engagement and usage.

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Case B: Loyalty offering optimization

The issue: ClientIQ was called to redesign the core loyalty program of our client, with the task to optimize the cost for the business with the perceived value from its customers.

The actions: Our strategy teams combined enhanced customer analytics methodologies with marketing research to measure the relevance of rewards programs and understand the attributes that impact customer spending behavior.

The results: The results of our proposal were dual, since in one hand, ClientIQ managed to improve the client’s financial performance by €1.7 mln, and on the other, improve customer satisfaction by 28%.

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Measure the real value of your customers!

Your customers can interact with and create value for your firm in a variety of ways. Companies often assess the value of their customers based solely upon their transactional activity. But is this methodology sufficient to provide the businesses with a deep insight of the value of their clients?

Case A: Lifetime value modeling to redesign the product palette

The issue: When our client called for our help, the business was infront of a great challenge. In view of an exclusive deal that had successfully negotiated, a deal that would result in significant financial benefits for the business, our client would have to discontinue the products of 70% of its clients. Our task was to formulate an end-to-end client management strategy that would minimize customer disatisfaction and attrition and would protect existing sales and revenues.

The actions: Trying to effectively address such a complex task, top priority for ClientIQ was to identify which segments to prioritize allocating the vast majority of our client’s resources. To do so, our analytics team calculated the internal lifetime value by customer (CLV), which was then correlated with the external lifetime potential. Based on the findings, the portfolio has been clustered into dinstinct groups with similar characteristics and needs, allowing our strategy team to set the appropriate business objective by segment and therefore formulate the most relevant marketing approach.

The results: Looking at the results of our strategy, one could immediately aknowledge the value of CLV modeling that ClientIQ introduced. Customer spending increased by 8%, generating €68mln incremental sales, while net revenues improved by 20%, generating €5.2mil incremental net revenues.

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Grow your customers’ spending depth!

Mining on customers' transactional data using basket analysis techniques, marketing and sales leaders are able to identify opportunities in segments with poor integration, and develop personalized marketing strategies that can lift sales volume by more than 10 percent, and improve ROI by five to eight times compared to mass marketing.

Case A: Improve customer Loyalty using the intelligence of marketing analytics in Retail Sector

The issue: ClientIQ was called by a retailer, to design its 12-months portfolio strategy, using the intelligence of customer analytics, aiming to drive business growth. 

The actions: Aiming to address the issue, ClientIQ developed a stepped approach. First, the analytics team performed a data cleansing and customer unification exercise, to introduce to the business a “single customer view”, while in parallel the strategy team proposed process enhancements related to the data retrieval practices followed by the business. Second, aiming to understand the speding patterns of our client customer base and identify key focus areas of growth, the analytics team performed a detailed portfolio spend deep dive covering portfolio segmentation & clustering, customer level basket analysis and sales trends, customer profiling with development of relevant marketing personas. As a final step, the analytics and marketing teams, redesigned the marketing strategy for the 2 prevailing portfolio segments of our client, using the intelligence of predictive analytics.

The results: Using ClientIQ’s structured approach and methodology, our client experienced a 6% increase in customer loyalty, 4% decrease of the inactive portfolio, 6% net sales growth compared to prior year, and 8% annualized sales growth.

 

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Case B: Basket Increase by expanding spending diversity

The issue: ClientIQ was called by a multinational credit card issuer, to design a targeted marketing strategy on engaged customers aiming to gain share from competition and attack cash transactions.

The actions: Using customer transactional history, basket analysis techniques and customer characteristics, ClientIQ analytics team developed a customer spending profiling tool based on which segments with low diversity have been selected for a customized marketing strategy designed to promote usage in underutilized areas of spending.

The results: Using ClientIQ's methodology, customers contacted increased spending diversity by 8% during the promotional period and 7% thereafter indicating a permanent shift in card usage patterns, resulting to a 23% uplift in their overall spending basket during the promotion and 13% in the following months.

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Improve your strategic plan through Predictive Modeling!

Predictive modeling is an excellent example where advanced analytics can be directly used to boost your company’s strategies. Whether you wish to attract new clients, promote new offerings to existing portfolios as part of your company’s cross-selling activities, retain customers or improve life-time profitability, knowing which segments to target and with what offers is key.

Case A: Optimization the cross – selling Strategy with the use of Predictive Modeling in Insurance Sector

The issue: Our client, a multinational insurance company, called ClientIQ to optimize the cross selling strategy for the bancassurance portfolio using the intelligence of customer analytics.

The actions: Combining predictive modeling techniques, with products and sales channels profitability analysis, ClientIQ analytics team identified the optimum handling cross selling strategy (“next best action”) by customer. Using the findings of the analysis, ClientIQ strategy team reallocated the cross – selling eligible universe across sales channels and products based on their ability to generate the maximum profit potential. 

The results: The new strategy proposed by ClientIQ lead to a 12% increase in the booking rate, 11% increase in the profit of new policies and 25% increase in the generated profit per sales offer.

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Case B: Marketing Budget Optimization with the use of Predictive Modeling in Retail Sector

The issue: Our client, a multinational retailer, called ClientIQ to optimize the allocation of its direct marketing budget to customers with the highest profit generation ability.

The actions: Analyzing historical performance data of promotional direct marketing campaigns that have been executed by the business, ClientIQ analytics team analyzed the positive & negative responders’ characteristics, and developed predictive models to measure customers’ probability to respond positively to an offer for the strategic product areas. Using the findings of the analysis, ClientIQ strategy team, allocated then the available marketing budget for all promotional actions, to customers with the highest profit generation ability  

The results: The new strategy proposed by ClientIQ lead to a 70% increase in the response rate, 40% increase in the net revenue and 45% increase in the net margin per targeted customer.

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Case C: Optimization of a Call Center Sales Strategy with the use of Propensity Models

The issue: Our client called ClientIQ to help improve the sales performance of its call center, one of its key contact points with its clientele and source of revenue. During the sales sessions, targeting of offers per customer was primarily based on the ability & experience of agents to diagnose the needs of the customer, which was far from optimum and in some cases also misaligned with the overall business strategy. Our task was to optimize targeting so as to maximize the sales potential of the channel.

The actions: ClientIQ’s teams addressed the issue holistically, employing advanced analytics with the use of Propensity Modeling to improve targeting and revisiting the sales management strategy to ensure successful implementation, sustainability and increased flexibility through close monitoring and tight sales management.

The results: Keeping capacity and monthly offers at existing levels, the new strategy, proposed by ClientIQ, lead to a 8% increase in the number of accepted offers, which in combination with the improved targeting to the most profitable ones (i.e. EBIT per offer increased by 33%), generated a net financial impact of €205,000 increased by 28%.

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Case D: Pricing Optimization through Propensity Modeling

The issue: ClientIQ was called to optimize the pricing of a time-deposits portfolio, aiming to imrove the deposits spread through reduction of customer rates, without putting at risk valuable customer relationships who had significant cross-sell opportunity.

The actions: Using advanced analytics and modeling techniques, ClientIQ’s strategy and analytics teams correlated customer profitability with the cross – selling probability and introduced a multi-segmentation approach and strategy.

The results: By implementing advance client management strategies, the overall deposits portfolio spread of our client increased by 80bps, generating an incremental impact to the business of €10mln per year.

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Case E: Acquisitions Targeting Optimization through Propensity Modeling

The issue: ClientIQ was called to optimize – with the use of predictive modeling – the acquisitions targeting on behalf for our client. Our task was to recognize among a list of prospect customers, those with the highest probability to respond and be approved with the ultimate target to optimize the bookings vs. cost ratio.

The actions: Analyzing historical data of similar past campaigns, and combining them with demographic and transactional data of our clients portfolio, ClientIQ’s analytics team identified the statistically significant attributes of profitable leads, isolating from the contact activity leads with low profitability dynamics.

The results: Based on the readings of our analysis, our client contacted 45% of available leads, excluding the remaining 55% from any contact activity, booking ultimately 87% of the total eligible population, with a cost that was contained at the 47% of the original amount, materializing savings of €182,000 and reducing the acquisition cost per new customer by 84%.

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Improve your company’s strategy through Portfolio Analytics!

Taking a portfolio approach to managing customer relationships, will help your company maximize its value, since it will help you as managers to effectively deploy customer acquisition, development, and retention resources on the segments with the highest ROI. Managing customers as assets is a long-term strategy that produces value.

Case A: Optimize strategic business initiatives in Retail Sector using the intelligence of customer analytics

The issue: ClientIQ was called by a multinational retailer, to assist on the optimization of its physical catalogue distribution strategy, using the intelligence of customer analytics.

The actions: Applying a combined view of basket analysis & GSIS analytics, ClientIQ’s analytics team measured the effectiveness of the physical catalogue distribution to generate incremental business impact by residence area. Based on the findings of the analysis, the team developed a revised catalogue distribution proposal prioritizing the distribution to residence areas with high profit generation ability and excluding areas with low or marginal impact.

The results: Through the revised business strategy developed by ClientIQ, our client achieved a 9% increase in sales with a 13% cost reduction resulting overall to a 25% increase in the revenue to cost ratio for this strategic business initiative.

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Case B: Design your marketing strategy using the intelligence of customer analytics

The issue: ClientIQ was called by a multinational retailer, to assist on the development of the overall marketing strategy of a specific business unit.

The actions: Applying a combined view of basket analysis & portfolio segmentation techniques, ClientIQ’s analytics team identified the prevailing trends, challenges and opportunities of the business unit in review. Capitalizing on the finding of customer analytics, ClientIQ’s strategy & marketing teams, developed in cooperation with the client, the set of strategic & tactical marketing initiatives, covering the areas of digital marketing, tactical direct marketing, quality research and offering.

The results: Through the revised marketing strategy, customer penetration to the specific business unit increased by 13%, basket size increased by 5%, resulting to an overall growth in revenues of 6%. Also by improving the targeting mechanism of direct marketing campaigns, the ROI has been increased by 3.5 times, setting the basis for budget optimization in future campaigns.

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Case C: Retention Process Optimization

The issue: ClientIQ was called to redesign the re-active Retention Strategy of a credit card issuer through its call center, focusing on Customer Equity maximization and resources optimization.

The actions: First call of action for ClientIQ's strategy and analytics team was to measure the life time value of every single customer of the issuer's portfolio and then classify the incoming attrition calls into segments based on the expected profitability. Second step, was to set the appropriate handling priorities among segments, i.e. the level of retention efforts and the appropriate mitigating offers. The above, were coupled with the design and the roll out of an enhanced infrastructure that could automatically provide customer information (i.e. segment and offering) on retention agents and an ongoing tracking mechanism to management, to monitor all stages of the retention process.

The results: Through the enhanced retention strategy, the credit card issuer managed to increase saved customer equity by 8%, while keeping retention unit's resources unchanged.

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Case D: Line Management Optimization

Regulatory changes, coupled with macroeconomic conditions may transform businesses. The credit cards industry is a great example that has gone through a tremendous transformation, moving from being one of the most profitable lines of business in banking in late nineties to a business that consumes equity and creates losses. The credit card businesses often fail to meet the ROE thresholds, with the most common reaction to the issue being the deleveraging of credit card portfolios, either by quiting the business altogether or imposing drastic reductions of the asset exposure. But is this the only solution?

ClientIQ – using advanced modeling techinques – can help you establish a methodology that will transform contingent liabilities and especially unused credit lines optimizing capital cost while revealing growth opportunities for your business.

The results: Applying ClientIQ's methodology for unused credit line management we helped our client release €1.2Mn (i.e. 3%) of its risk capital and materialize a €4.2Mn net financial benefit.

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