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Historical promotion analysis is the most significant strategic action area for retail companies in their quest to adopt or improve their existing optimization goals for promotions (Figure 4). Firms displaying Bestin- Class practices consider improving their abilities for historical promotion analysis as a key step in improving future promotion accuracy and profitability.
Our standard for measuring Best-in-Class performance reflects the demands of shareholders and consumers alike; we combined year-over-year comparable sales (stores and all other channels), margin for featured and complementary products (in the past 2 years), customer retention (in the past 3 years) and market basket size (in the past 3 years) as a percentage improvement of sales. Best-in- Class retailers manage to accomplish top tier performance in all of the above metrics. Best-in-Class retail enterprises that have currently adopted promotion optimization applications take into account the successful and failed promotion data from the past for an accurate processing of a promotion mix. Best-in-Class (71%) believe that historical promotion analysis is a key strategy for their promotion optimization process. More than half of the Average (59%) and close to half (45%) of Laggard companies consider this strategy as important for optimization.
A key component of any historical promotion analysis is dependent on effectively measuring the adoption of new branded or own-brand merchandise. Tracking new product adoption enables enterprises to predict profit uplift for a category and capture the best promotion mix for a particular promotion period. Best-in-Class companies outnumber the Average and Laggard when it comes to tracking new product adoption for measuring promotion effectiveness. While 86% of the Best-in-Class track new product adoption, only 42% of the Average and 33% of Laggards are measuring this critical metric. Thus, the Average and Laggard are building a major barrier in their ability to plan effective promotions and bottomline profit.
Standing in the way of optimized promotions are challenges related to promotion data aggregation and validation. Half of the retailers’ feel that their teams are constrained by their quality and quantity of reporting (Table 1). All too often, retailers face hurdles in aggregating large amounts of data and producing timely reporting. Spreadsheet based non-automated promotion reporting systems, which are used by more than half the retailers’ (57%) use insufficient metrics to gauge and improve optimization performance. Organizations are dealing with lack of clean data, lack of adequate customer information and scattered data across the enterprise.
Nearly half (47%) of the GMA retailers’ face an uphill task as they either do not have clean data or they lack specific customer data for generating valid results. Companies are responding to the challenge of data aggregation by bringing in outside consultants to help with data cleansing projects and align incentives to the promotion process results. As far as finding the balance between data aggregation and strategizing/optimizing, an increasing number of retailers are selecting smaller cross-functional teams and projects to test promotion results. Supermarket and grocery companies attest that they are bringing in outside help (58%) and one-third (33%) are selecting smaller cross-functional teams for implementing the promotional processes including analytics in an effective manner.
As shown in Table 2, survey respondents fell into one of three categories – Laggard, Industry Average, or Best-in-Class — based on their characteristics in four key categories: (1) process (ability to address exceptions, responsiveness to customer needs, effectiveness metrics in place); (2) organization (collaborative strategy, design expertise, and level of collaboration among stakeholders); (3) knowledge (enterprise data management strategies, visibility and near-real time process management); and (4) technology (infrastructure excellence, analytics and performance improvement). In each of these categories, survey results show that the firms exhibiting Best-in-Class promotions optimization technology usage characteristics also enjoy Best-in-Class customer and financial performance (Table 2).
Across all surveyed retail industry categories, promotion optimization adoption was found to be increasing. Respondents were asked for their likely investment in specific value-chain areas within their retail organization, as promotions have a cross-value-chain impact. These results are listed in table 3. According to our findings, respondents indicated that implementation or access to features of promotion optimization solutions, such as analytics or promotion calendars, would be provided in departments such as strategic planning, marketing, inventory management, pricing and store operations.
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