Client: Global consumer electronics manufacturer
Business need: Determining the optimal mix of short and long-term marketing activities to achieve sales growth and increase marketing effectiveness
- Developed and implemented a market mix model that attributes historical marketing activity to sales data, and allows “what-if" simulations to evaluate future spend scenarios for likely sales impact
- Entire analytics “stack" from data collection through findings development, visualization, and forward planning simulations
- Quantified “halo" impact of marketing spend on one category on others within the same master brand
- Optimized allocation of marketing spend and improved scheduling of marketing initiatives
- Quantification of the sales impact and ROI of marketing/promotional spending
- Fact-based predictions on optimal activity mix, spend levels, and scheduling for maximum ROI and sales
- $57 million increase in annual sales for the color television category
- 3x higher ROI from changing tactics on media spend
Consumer electronics marketers struggle in choosing between short- and long term marketing activities due to inadequate understanding of the associated impact on sales. Harnessing data across channels and functions for predictive analytics helped this consumer electronics leader optimize its mix of marketing activities to boost sales.
The consumer's path-to-purchase for consumer electronics is substantially longer than that for other consumer goods. The relatively short life cycles for new models and features also results in consumers fearing that they might make a “less than optimal" purchase. This perceived risk impacts sales and makes determining the proper mix of long-term brand building and short-term marketing activities a daunting task. Today's consumers are also exposed to an expanding, fragmented array of marketing touch points across media and sales channels, each of which generates massive amounts of data. Most organizations struggle to harness the volume and velocity of this data when they are assessing the interplay of long-term brand building and short-term activation activities to plan spend and marketing execution.
This consumer electronics leader invests significant spend across traditional and digital media, including retailer ads and price promotions to influence sales. However, the company was unable to reliably and consistently measure—or predict—the impact on sales. A largely backward-looking analytics approach treated marketing and promotional tactics in isolation. Making matters worse, different teams, agencies, and media buyers were operating in silos, and using different methods of measurement. As a result, the company wasn't able to precisely determine how all the moving parts of the total marketing plan collectively drove sales, nor what would happen when they adjusted them. This led to inaccurate attributions affecting sales outcomes, return on marketing, and media spend.
A team of data scientists worked alongside analytics, process, and marketing experts to provide objective insights into short- and long term marketing effectiveness and ROI. They collaborated with the company's marketing teams and agencies to adapt marketing mix methodologies that matured in the consumer packaged goods industry, in the specific context of long-purchase-cycle consumer electronics.
First priority was to get a consistent view of existing activity and spend. To do so, the experts analyzed multiple data sources for accuracy, quality, and currency of the data on marketing and promotional activities, as well as sales to consumers. A broad range of relevant data for the most recent 152 weeks was collated by coordinating responsibility for different portions of the go-to-market plan with various teams, including market and global teams, demand management, product marketing, media and agency partners, and retail customers.
A market-mix model was developed to establish the quantitative relationship between sales and various promotional and marketing activities. The analysis isolated the impact of individual variables on sales in the short term, and identified the long-term impact of the previous year's spending on current sales. The model also measures the impact of a wide range of other factors—competitor activity, price changes, environmental factors, innovation, etc.—on sales.
Genpact modelers used best practice methodologies to ensure accurate and reliable findings, with particular attention to the findings being not only descriptive of current impact, but also predictive of future impact.
Finally, “what-if" simulations evaluated future spend scenarios for likely sales impact and helped predict the potential outcomes from adjusting individual activities and variables.
The company can now simulate alternative media and promotional plans with a high degree of accuracy, and optimize them prior to execution. Using the findings and response curves, the company identified multiple opportunities to improve sales by optimizing marketing and promotional spends, tactics, and scheduling by:
- Using digital media (display, search, online video) more effectively as it offered a much higher return compared to traditional media (TV, magazines)
- Better alignment/scheduling of media spend to seasonality of sales, increasing overall sales impact
- Determining the minimum and maximum levels of weekly spend most effective for each activity
- Adjustments to weekly scheduling and day-part (more cable day-part) execution could boost ROI on TV media
- Deploying programmatic digital media buy strategies
- Optimizing retail price discounts, and scheduling retailer merchandising events that have become the largest contributor to current sales
- Calculating the upside of more aggressive spend strategies—for instance, a $20 million incremental investment in key media would result in a sales increase of $172 million
The company is on track to implement these changes, with early results showing a $57 million increase in sales in the color television category alone. Similar results are expected in other categories, such as mobile handsets and home appliances. The company, which has boosted ROI on spending on television advertising by 3X through more scientific scheduling, is now better positioned to respond to changes the marketplace, such as campaigns, retail promotions, or new product launches by competitors, faster and with greater precision. A consistent and predictable view of the ROI of marketing spend helps the organization allocate funds judiciously, and avoid over- and under-spending on critical enablers of its sales and future growth.