What is CPG data analytics?
Consumer Packaged Goods [CPG] data analytics is the compilation and analysis of multiple data points that are the result of sales marketing actions. Understanding the data collected helps CPG research companies recognize patterns and make sense of market trends which in turn offer nuanced CPG insights.
Table of contents
- CPG data analytics is obtained from:
- How can CPG analytics improve efficiency?
- Important CPG data analytics KPIs
- Leveraging CPG analytics
- The cycle of continuous improvement
- The Road Ahead
CPG data analytics is obtained from:
This includes the in-store conditions the reps observe and report from the field. The data obtained provides a comprehensive idea of the in-store execution and the opportunities discovered during the site visit. Sample metrics include:
- Stock levels
- Number of facings
- Competitive activity
- Promotional compliance, etc.
This data includes the specific in-store actions by the team.
- How often are the reps visiting their various accounts?
- How well are the reps covering their territory?
- What are the most frequent actions the reps deploy in-store?
Compiling this data helps understand the specific actions taken by on-ground teams to improve in-store execution. Estimating and monitoring these actions is essential to understand the actions with the greatest sales impact.
As the name implies, this data is straightforward – how much of each product is sold at individual stores over a specified period. This data, in conjunction with the above two data sets, provides insights into the activities and store conditions that lead to the highest sales.
How can CPG analytics improve efficiency?
Tracking the above three types of retail data helps equip the team to address:
- Which products are out of stock and where?
- Relationship between visit frequency and sales efficacy
- Relationship between compliance and sales performance
- Stores that typically do/don’t maintain compliance
- Which typically high-volume stores have low sales?
- Which stores haven’t been visited by a rep yet this month?
Forecast consumer activity
In most cases, an out-of-stock situation could have been avoided by tracking the data. CPG analytics can be leveraged as a predictive tool to let teams know the current stock levels so that products can be replenished before they run out, preventing customers from opting for a competitor’s product.
With a long-term analytics strategy, CPG research companies can recognize patterns with different retailers and predict when to replenish the stock, minimizing the stress over inventory management. For instance, CPG research tools offer excellent insights into consumer activity.
Ensure display compliance
Retail execution needs to ensure optimal in-store displays and retailer compliance. While CPG displays can improve sales by as much as 193%, they’re executed to compliance less than 50% of the time.
Ingenious CPG brands employ data analytics for recognizing non-compliance to get back lost sales. For instance, CPG brands can monitor store sales with a secondary display to assign baseline metrics for the heightened sales expected from promotions across specific products. The baseline data after the promotional offers will clear up if the problem was due to the display setup or location.
CPG research companies can help CPG brands act on those target accounts through their field teams. With POS trends, brands can initiate data-driven conversations with retailers and implement corrective steps for the displays through CPG research tools.
Let data drive the story
One of the challenges CPG brands face is getting their product on store shelves. Instead of the archaic trend of relying on anecdotal testimonies, CPG research tools are of great use in these contexts to show hard data and analytics to convince retailers.
Data-driven CPG insights are easy to understand when communicated clearly with minimal jargon.
KPIs are a set of metrics decided on by the team and can focus on things like sales volume and expansion, rep visits over a specific period, fresh and churned accounts, and more.
KPI data offers insights into what needs to be addressed in the field to boost performance. Once KPIs have been tracked, analyzing them will offer nuanced CPG insights into team efficiency and areas of improvement. CPG research tools can be leveraged for analysis to generate actionable CPG insights.
Also Read: Food Industry Market Research
Important CPG data analytics KPIs
Here are some high-performance KPIs CPG brands must focus on when performing analytics.
Product promotions are an incredible way to boost sales. Everyone loves discounts! However, it is vital to measure trade promotion effectiveness. Promotional datasets are
- Incremental (Sales attributed to the promotion)
- Non-incremental (Sales that aren’t part of the promotion)
Determining if a retailer isn’t executing a promotion requires filtering the data down to a smaller demographic such as a specific market/region, to identify the problem. At this point, CPG brands can reach out to specific retailers and address the problem.
Comparing multiple datasets allows for determining the efficacy of promotions and demonstrating where specific changes can be made.
Market category share
The retail market today has competitors in every category. Obtaining data on the market share within specific categories can help CPG brands understand where they fit into the broader market and if aggressive expansion is possible.
When looking at specific categories, it’s integral to understand the various features that influence the category. For example, an energy drink feature such as ‘can size’ and its influence on sales outcomes. This allows CPG research companies to provide data-driven decisions on increasing the brand share of the category.
Small CPG brands often get overwhelmed. However, establishing characteristics and the driving forces behind sales growth will help CPG brands understand how to make the best of them. For instance, if a specific size of energy drink sold more than the other, stocking that in higher numbers or adding this product to the portfolio will help.
While one-timers will be prevalent, loyal shoppers will expand business in two ways. They buy specific brands/products repeatedly and inadvertently become brand ambassadors talking about the product within their circle.
When measuring loyalty, there needs to be a distinction between the number of brand loyalists vs. one-time shoppers vs. switchers (customers buying based on product and not the brand).
- What factors drive loyalty to a competitor CPG brand?
- What can be done to foster the same loyalty to your CPG brand?
For instance, if a CPG brand category has considerable switchers, there’s ample opportunity to foster loyalty. CPG brands can appeal to the switchers after understanding the target demographic to get them to start buying their products exclusively.
Also Read: Food Industry Research and Development
Leveraging CPG analytics
CPG data analytics must provide insights into the growth opportunities available and how resources can be optimized, reducing wastage and loss. Random, well-intentioned modifications without any basis may simply hurt the CPG brand more than help it. A cycle of continuous improvement can be deployed with data-driven CPG insights.
The cycle of continuous improvement
After analyzing and compiling the data, the next step is to use the data within a cycle of continuous improvement that will help brand expansion.
The continuous improvement cycle propels peak performance as it allows field teams to continually and consistently improve. Every action in the field is advised by
- Real-time data
- Current store conditions
- Results of past campaigns on sales
Using CPG research tools empowers brands to deploy the insights obtained in the planning stage before driving actions in the field. The cycle of continuous improvement includes:
At a macro level, every action in the field begins because of certain insights. A CPG insight indicates an issue or an opportunity in the field that must be addressed to maximize sales.
This stage comprises examining past performance to:
- Address past pitfalls
- Determine the team to be deployed when and where to streamline the process
- Figure out the steps to be implemented in the store to produce the highest impact
In this stage, the sales reps execute the plan in their targeted accounts and report the in-store conditions influenced. The data generates feedback into the CPG data set and advises the subsequent insights that begin the cycle again.
The cycle of continuous improvement helps:
- Teams to implement the right action in the field at the right time
- Maximize the efficiency and sales impact
The Road Ahead
At Spoonshot, we are constantly helping food brands, start-ups, and corporate giants, figure out their next big launch. We do this by connecting apparently disconnected data points to
- Discover current ingredient favorites
- Figure out the next big trend
- Understand the direction of customer expectations