CPG Solutions

Analytics value across the value chain

We help CPG companies increase revenue, share and margins by efficiently and effectively applying a wide range of advanced analytics capabilities tailored to each business need. Capabilities include:

Assortment Optimization
Marketing Optimization
Price & Promotions Optimization
Consumer Segmentation
Driver Analysis Using SEM/BBN
Known Value Item Analysis
Design of Experiments - Media Testing
Digital Marketing Measurement & Analytics
Shelf Space Optimizaton
Brand Club & Direct-to-Consumer Analytics
Choice Modeling

Assortment Optimizationgo to top

Business Problem: The number of SKUs that retailers carry has increased exponentially over the years. The average grocery store carries between 40,000-60,000 SKUs. While this increased choice is valuable to consumers, it also causes confusion in their minds. SKU proliferation is a big source of cost escalation for manufacturers and retailers because of the complexity it creates in manufacturing and supply chain management. Retailers and manufacturers both want to understand which SKUs add incremental sales and whether the incremental sales justify continuing the SKU.

Solution: By applying analytics to POS and panel data, companies can measure the incremental demand that a SKU addresses. This is also known as demand transferability. In other words, retailers and manufacturers are trying to understand if a particular SKU is not present, will consumers buy another product (transfer the demand), or will they go to another store to purchase the product.

Deliverables:

• Estimation of incremental demand generated by SKUs
• Identification of SKUs that have high incremental demand and must be kept in stock
• Identification of SKUs that have low incremental demand and can be eliminated without losing incremental sales
• Assessment of net impact on sales by eliminating a SKU
• Recommendation of which SKUs to keep and which to discontinue, with associated cost benefit analysis

Marketing Optimizationgo to top

Business Problem: Marketing managers are accountable for marketing budgets, and generating ROI from the same. They need to keep improving efficiency in not just the allocation of marketing budgets across marketing levers, but also in the execution of marketing activities. They also need to continuously test and measure the impact of new initiatives for their brand or portfolio of brands. For better planning, they also need to know the impact of various what-if scenarios, including the impact of competition.

Solution: Through Marketing Mix Models, we measure the impact of various marketing activities on incremental sales. Using the models, we segregate the sales impact of individual marketing activities and identify ROI from each, and thus design better marketing plans. With the help of MMM, we optimize the marketing mix for the brand or portfolio of brands, for future marketing activities, in order to maximize revenues/ profits.

Deliverables:

• Historic assessment of brand/category and marketing activities by the brand and competition
• Sources of volume and drivers of sales
• Assessment of various marketing activities - effectiveness and ROI
• Optimized media plans and execution
• Optimized marketing spend allocation
• Specific growth opportunities for the brand
• Simulation and optimization tool

Price & Promotions Optimizationgo to top

Business Problem: Pricing is one of the important decisions for a CPG marketer. In the age of hyper-competition, fluctuating commodity prices and increasing retailer power, it is important for the CPG company to understand how its product pricing is processed by its consumers in the context of competition. Also, trade funds constitute a large part of overall marketing budgets. And it is increasingly becoming important for the marketer to identify the most impactful promotional strategy.

Solution: We develop regression/bayesian models on sales including price, promotions, distribution, seasonality, etc., to isolate the impact of different price and promotions strategies deployed by the brand in the last 2-3 years. Price and promotional elasticities are then used to build product portfolio strategy to develop the overall pricing strategy for different variants of a brand. We also identify the impact of competitive price changes to build effective competitive strategy. The inputs are used to develop price tiers and price bands/corridors, to help marketers effectively price their products. Simulation and optimization tools help in deploying these analytics strategies within the decision environment.

Deliverables:

• Overview of category, price and volume trends; key observations like studying overall market with respect to different markets through visualization dashboards
• Price sensitivities of products due to own or cross pricing
• Promotional effectiveness
• Impact of threshold points and gaps
• Price corridors indexed to competition
• Optimized promotional plan
• Simulator-optimizer-tracker tool

Consumer Segmentationgo to top

Business Problem: For any product or service, the overall group of consumers is a combination of various distinct subsets. These smaller sets of consumers are distinct in terms of their needs, behaviors, and attitudes towards the brand or category. Businesses need to identify these specific sets and understand each of them distinctly to unlock the potential of every consumer – by better targeting in the form of placing the right product and the right offer for the right customer.

Solution: Consumer segmentation using consumers' profiles or their behaviors or attitudes helps identify distinct set of consumers, and gain deeper insights on the WHO, to better shape the opportunity by understanding:

• Underlying needs, attitudes and motivations, current behaviors
• Practices/alternatives
• Brand perception/rating vs. its competitors
• Purchase behavior – what they buy, where they buy

It also helps determine which need areas to pursue and leverage as a foundation for concept/product development.

Deliverables:

• Identification of distinct segments
• Profile of each of the segments
• Classificition algorithm and tool for new set of consumers into the defined segments

Driver Analysis Using SEM/BBNgo to top

Business Problem: Within any product category, there are ample choices of brands for consumers to buy, and there are a lot of distinct factors that influence the choice of brand for these consumers. Within these factors, there are few key factors that significantly drive the brand preference. Businesses need to identify these factors and ensure that their brand positioning aligns with those - to be in the set of preferred brands.

Solution: Driver analysis using SEM or BBN plays an important role in identifying the purchase preferences of consumers. Using the equity scan data or the concept test data, we can identify the key drivers (among many equity measures or product characteristics) that significantly drive the overall rating or purchase intent of the brand. These key drivers can be incorporated into future product design, brand positioning, or communications.

Deliverables:

• Identification of key brand drivers
• Relative significance of each of the factors
• Assessment of brands in terms of their perception on the key factors
• Opportunity plots for each of the brands - identifying key strengths and key areas of improvement
• Communication and brand positioning strategies for the brand

Known Value Item Analysisgo to top

Business Problem: Shoppers use the prices of a few items in a store to form a value perception about that store. If the CPG company/retailers know these items, they can develop pricing and promotion strategies to earn greater profits and, at the same time, build a strong value perception in the market.

Solution: We integrate the trends from historical POS data and decode the price-volume relationships for different items. This analysis is then combined with market research data to understand the awareness and use of the prices of different items in making store choice decisions. Once we identify KVI items, we perform pricing threshold analysis to identify the "right price" for these high impact KVI items.

Deliverables:

• List of KVI items and non-KVI items
• Driver analysis identifying key characteristics of KVI items
• Threshold price for the KVIs
• Volume impact due to crossing thresholds for KVIs

Design of Experiments - Media Testinggo to top

Business Problem: Consumer products companies want to test new products, pricing and promotion strategies, merchandizing strategies, etc. within their retail channels. Typically, they would introduce these over a subset of the retailers' stores and, depending on certain success criteria, they would make a decision on whether to scale these across all the stores/channels or not. CPG companies want to understand how to identify a representative sample from a set of stores. Also, the sales of a brand at a store depends on a lot of different variables, and it is hard to single out the impact of a specific strategy on overall sales. CPG companies want to be able to measure the impact of tests conducted on key KPIs, and to define the success or failure of the test.

Solution: We use historical POS data, in conjunction with demographic data, to identify test and control stores which trend very similarly, and which are also representative of the market being studied. Comparison of sales data pre- and post-test between test and control stores would give a measure of the impact of the test. Demand models can be created against historical POS data, which would enable adjustment of the sales data for differences in pricing, promotions, merchandizing, etc. between test and contol stores.

Deliverables:

• Test setup specifications like test store selections, and test control pair identifications
• Test effectiveness and outputs
• Simulator to see the impact of the test in different market scenarios/geographies

Digital Marketing Measurement & Analyticsgo to top

Business Problem: Digital media is becoming increasingly important for marketers today. Having invested in social media/websites/email marketing, and also investing in measurement platforms like Omniture, marketers still struggle to identify the right metrics to track the effectiveness of their digital marketing efforts. The other challenge is to understand how to integrate overall marketing planning for their brands, which includes traditional and digital medium.

Solution: We integrate web analytics data with the other data available to solve the overall marketing planning problem for marketers. It includes understanding the ROI from an email campaign versus a TV campaign. Also, identifying the right digital mediums to invest in for the brand, by analyzing past digital campaigns.

Deliverables:

• Integrated dashboard for digital and traditional medium for marketing planning
• Synergy analysis across mediums

Shelf Space Optimizatongo to top

Business Problem: Consumer packaged goods and retail companies want to understand the optimal space allocation of a category, brand, etc. in different departments within a store to maximize the shelving condition. They would also like to understand the impact of maximizing the shelving condition to growth in revenue.

Solution: Re-arranging the shelf space configuration through simulated scenarios for various categories and sub-categories using pre-defined business parameters can help clients optimize the shelving conditions of a category, brand, etc. in different departments within a store. This also includes building algorithms for pre-tracked business parameters, and identifying growth opportunities through regression modeling and optimization.

Deliverables:

• Optimizer to provide optimal shelf space allocation strategy to maximize shelving conditions in a store
• Simulator to generate optimal space allocated to each category, and the change in space from the current allocations
• Impact of maximizing shelving condition to growth in revenue

Brand Club & Direct-to-Consumer Analyticsgo to top

Business Problem: Rise of social media, challenges with TV advertisements (i.e. DVRs), increasing brand promiscuity among consumers, and increasing competition is pushing marketers to look beyond traditional avenues to build consumer relationships. In this context, direct-to-consumer marketing is becoming increasingly important for brands worldwide. Marketers, especially of high-involvement category products, are using brand clubs and direct-to-consumer programs to forge higher impact relationships. They are looking for analytical tools to leverage the rich data that these clubs generate, and effectively use it for high investment marketing programs.

Solution: Using the consumer-level data and the syndicated data available with CPG companies, we provide the following solutions:

• New insights about consumer behavior using segmentation
• Customer lifetime value models to better leverage these relationships
• Understanding the drivers of brand loyalty and switching behavior

Deliverables:

• Segmentation handbook based on consumer level data
• Loyalty and switching drivers analysis
• Predicted customer lifetime value models with cross-sell and up-sell opportunities identified

Choice Modelinggo to top

Business Problem: The decision-making process of consumers is complex. It is important for brands to understand how different factors come together to influence consumer decisions. Marketers want to understand which is the most potent combination of various product attributes that will maximize consumer acceptance.

Solution: We define and model the decision process of an individual or segment in a particular context and predict how individuals would react when presented with a particular combination of propositions. For example, price, features, or pack size combination. We also determine how much are consumers willing to pay for an improvement in quality or product features.

Deliverables:

• Recommendations on the most potent proposition for target consumer segments
• Market share estimates of different product feature combinations
• Utility scores for each attribute