In the era of digitalization, one might wonder if promotional activities based on printed leaflets possess the impact they had in the past or whether there are customers more prone to be responsive to this type of engagement.

Accordingly, our client, a retail company, was seeking help to redefine its promotional leaflet distribution strategy.

The main goals were to increase store traffic and conversion rates while maintaining the current budget spending which limits both the leaflet number and distribution zones.


The first step was to understand, at the customer level, which segments reacted best to the printed leaflet distribution through pilot testing. To assess the impact of the distribution strategy, a control group, who did not receive a leaflet was established in every distribution cycle. Then, our predictive model benchmarks people with similar characteristics from the test and control groups to quantify which are the customers more sensitive this type of contact.

The impact estimations were incorporated in an optimization model to determine the ideal zones and leaflet number to be distributed.


By evolving decision-making from a purely empirical and static standpoint to a data-driven process, our client can quantify and understand the effects of targeted promotional activity on different receivers.

The project reaped benefits by maximizing positive customer engagement with the leaflet leading to increased sales and optimized advertisement costs, while minimizing unnecessary resource usage. Keeping the same budget, we were able to obtain an additional return of 14 cents for each euro invested. The implemented model was internalized at the client, enabling autonomy from the team and allowing the creation of long-term value.

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  Increasing loyalty by executing customer retention and acquisition promotional campaigns has been one of the main marketing objectives for the last decades. While marketing and commercial teams work hard to deliver the best value to customers, the brand-customer relationship is becoming more dynamic and multi-layered with customers having increased competitor awareness and preferring to use proximity stores to cherry-pick shopping baskets.   Whether on retail, banking or any service companies, the strategical planning of loyalty targeting and promotional activity is becoming a very complex task which, if not built upon solid profitability evidence, quickly turns into a  resource-usage and margin-diminisher managerial problem. While the promotional strategy is typically enforced on a top-down matter, the customer response complexity and dynamicity urge a bottom-up approach that manages to ensure one-to-one ROI focused on real customer needs and basket growth opportunities. 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While RFM models have very valuable predictive power and provide a simple but effective way of segmenting customers, they fail to pick up on the necessary consumer behavior detail to fully optimize the marketing relationship. One could dive even deeper and find such different behaviors within the same customer, perhaps across different product categories. Multi-product companies typically face very different competitors across their assortment range, and customer retention and churn measurements should also include this diversity dimension. Otherwise, the company may never extract the full potential from its customers and may be losing more money than they even realize. Broad lifecycle segmentation is no longer enough to respond to the evolution of customer loyalty, as companies need to figure out the driving needs for customer shopping and understand their true potential value and, ultimately, profitability. 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Developing these predictive models enables companies to avoid the most common mistakes of promotional planning: Focusing on quantity instead of quality: Having too many promotions will, at most, maintain customer’s cost perception while eroding most chances of sustainable profitability; Ignoring customer data on the promotional definition: Suppliers are the main source of promotional funding, but the value of such mass promotions are limited regarding the impact of customer growth and acquisition. When strategic guidelines are spread down from general segmentations, customers may end up getting targeted for promotions they don’t need, on channels they don’t respond to, and with a disproportionate value regarding their potential brand engagement. The only way to avoid this issue is to strategize not on the promotion and channel usage, but on how different customers should be targeted. 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The combination of an increasing relevance of the online channel and the power of advanced analytics has brought new opportunities for COOs (Chief Operating Officers) to position their departments as value centers. In this context, the concept of ‘value of service’, e.g., understanding the net impact of providing same day deliveries, emerges as a powerful tool to improve the clarity of discussions in organizations and to bridge the gap between marketing and operations. This paradigm contrasts with the traditional positioning of having operations merely satisfying marketing requirements at the lowest cost.  For years in the offline channel, the dialogue between marketing and operations was often dominated by the trade-off between in-stock rates and inventory turnovers. In the online channel, the natural extension of this organizational posture was to add speed as another performance indicator. This reactive stance hindered the fact that operations are even more central in this online world and that more value drivers (such as quality of packaging, preciseness of delivery, and flexibility of delivery slots) become as important to factor in the aforementioned dialogue. More interestingly, the rising power of advanced analytics makes it now possible to anticipate the quantitative relation between value drivers, customer lifecycle value and supply chain costs — ‘value of service’, avoiding misunderstandings and therefore, providing more alignment within the organization. Customer expectations in the online setting have made it hard for companies to find a way to break-even. By acknowledging the ‘value of service’, it is possible to increase the pace and efficacy of testing new service models that may result in a future competitive advantage. Moreover, better service trade-offs can be attained by discussing simultaneous levers, such as supply chain costs and delivery lead-time. To apply this idea, cross disciplinary teams involving operations, marketing, and analytics members must be set up to jointly determine the value drivers to analyze, the success metrics to use and the most suitable methodologies to apply.   We have performed extensive consulting and research with online players and other companies in different retail sectors. In a particular case, after performing several econometric analyses, we ended up justifying the opening of several distribution centers, based on the increased revenues they would generate through better packaging, delivery preciseness, and improved lead times. The work of Marshall Fischer and others (Marshall L. Fisher, Santiago Gallino, Jiaqi Xu, 'The Value of Rapid Delivery in Omnichannel Retail') was a stepping stone in terms of methodology and scope to pursue a central idea — there is a hidden opportunity of improving e-commerce businesses when understanding operations as a top-line enabler. Written by Pedro Amorim (LTPlabs’ Co-Founder & Professor at Faculty of Engineering of the University of Porto) & Paulo Sousa (Manager at LTPlabs).


The corporate world has been embracing analytics and artificial intelligence systems within an increasing number of business functions that have traditionally been oblivious to its potential. Additionally, the digitalization of the customer journey is increasing the amount and detail of data that can be accessed, which provides tremendous value towards decision-making and personalization efforts when properly addressed. These new possibilities pose several challenges throughout the marketing mix that require an ever-increasing pool of analytical solutions. Therefore, companies that do not adopt these techniques within their processes will soon become outdated and lose market competitiveness. In addition, the deployment of analytical tools to the different marketing functions will increase marketers’ decision-making quality by empowering them to deliver the right product at the right price and at the right place to the right people. 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