How To Properly Implement and Iterate Your Revenue Growth Management

While more and more companies are utilizing revenue growth management in some capacity, it’s important to discuss the fact that there are different trends in the CPG segment shaping how they approach it. Here are some of the key examples that we see as of right now.

One thing that propelled the need for revenue growth management to a different level was the growth of digital media. Suddenly the number of different consumer touchpoints had grown exponentially, to include items like:

• Smartphones
• Social media
• Brand websites
• Online marketplaces

All this, and you still have brick and mortar to consider. Many conventional methods of promotion planning and optimization started failing largely because there were simply too many new customer segments to look into. For example, customers that largely buy through online marketplaces may not be swayed by a loyalty program the same way brick-and-mortar customers are. Applying the same promotions for both segments would hamstring your efforts.

Two main changes have come out of this trend:

• Data-driven marketing practices, based on learning about these new segments.
• Micro-targeting with promotions to get higher conversions.

Readjusting the greater strategy to accommodate these segments is a clear example of revenue growth management in action. This helps you be more agile and customized with your promotions to suit all customers.

Statistics show that 87% of major companies suffer from what is known as “growth stalls,” a material decline in company revenue. Those companies that suffer a stall lose as much as 74% of market capitalization compared to their counterpart over the following decade. Revenue growth management ensures that there’s always some sort of increase in profit to outpace that statistic.

The role of AI in CPG fits neatly into a greater focus on revenue growth management. The biggest concrete benefit of AI in its current state is helping your teams spend less time on tedium and number-crunching, and more time on interpreting data and high-level strategy. This high-level strategy, based on data, is exactly what revenue growth management is supposed to be. 

For example, say that you needed to look at customer behavior in order to analyze the success of a promotion. Without AI, your team would need to gather the data from whatever software or collection methods you have, organize it to determine what customers used the promotion, and gain insights from there. AI enables you to skip those first two steps. In addition, AI can quickly organize your customer segments by:

• Demographics
• Shopping frequency
• Region
• Accompanying purchases
• Registration to loyalty programs

Perhaps the biggest benefit of AI, though, is the potential for data harmonization. Collating data for a single promotion is hard enough. Doing that for multiple promotions across different segments is a nightmare. However, AI makes this possible for those small to mid-sized CPG businesses. Triangulating customer behavior is the key to creating a high-level strategy.

However, we have also been critical of AI/machine learning in the past, and some of the issues then still apply. For example, AI is only as good as its base data. In addition, there are some essential metrics like SKU elasticity, brand loyalty, and brand equity that are hard for AI to properly collect data on. Treat it like any other business resource for now, with its pros and cons.

Technically, every CPG company is using some sort of revenue growth management strategy. After all, they probably have goals for their trade promotions and pricing plans, and to a degree, that applies. However, there are lightyears of difference between base goals and concrete strategies. Here are some of the common mistakes companies make in the formulation and execution of revenue growth management.

Not powering their methods with tech

Some companies are still using manual spreadsheets to house their data, and it’s impossible to get into revenue growth management at that level. Instead, you need to start investing in advanced capabilities. These include:

• Predictive outcome generation
• Advanced analytics
• Data harmonization

Because of the higher scale that revenue growth management runs at, you need systems that can properly handle it.

Incomplete Information

Optimizing trade spend is great, but you need to make sure that you have a full picture of what your trade spend is first. If you have minimal analytical capacity or data, it’s hard to properly understand the return on investment you get with trade promotions.

In addition, this information is also needed to create guidelines for your sales planning and customer teams. At a minimum, you need:

• Net unit costs
• Optimal frequency levels
• Ideal windows for promotions

Lack of accountability

While revenue growth management is largely about data, it’s still people processing and analyzing this data. For many CPG companies, it’s not clear who has what responsibilities. This is a major issue for revenue growth management because it requires different teams to communicate with each other. Make sure that everyone’s roles and responsibilities are clearly defined before moving forward. 

Along with this, you also need to create a formal process to monitor your trade spend. Revenue growth management is as much about reinforcing what you have as it is introducing new data and metrics.

Not going far enough

This one may come across as a bit of a surprise, but the fact is that many CPG leadership teams make the mistake of thinking they’ve “mastered” revenue growth management where they are really just adopting the basic core principles. Taking things to the next level generally entails going through one of three paths:

Strategic RGM: Trying to improve long-term value creation as well as focus on growth in different categories.

Precision RGM: Bringing in new analytics/data sources to create better strategies for pricing and promotions.

RGM Scaling: Expanding revenue growth management strategies across an entire organization, versus just one product category or segment.

In an ideal world, a company would be able to take all of these on at the same time. However, there’s always going to be limits on data you have to work with and organizational bandwidth. Leaders need to make a hard, data-based decision on which of these pathways they take after establishing a base for revenue growth management.

Regarding that last point, CPG companies may be wondering which of those three paths is best for them. The ideal way to illustrate that is through data. Here are some metrics and case studies that provide some concrete facts on revenue growth management, and the ideal methods to use.

Concrete Benefits

Statistically speaking, a properly modernized revenue growth strategy can generate benefits equal to 3-5% of gross profit. This can be huge for companies trying to get every last bit of profit to appease investors.

Case Study: Promotional Analysis Practices

In one scenario, a large CPG company was working to improve its promotional analysis work. However, when linking brand strategies to promotions, there was a breakdown in communication. The end result was repeated static promotions with diminishing returns. In order to improve this issue, a major consulting firm had the company:

• Reference shopper metrics when allocating promotion funds
• Look more holistically at the impact of spend shifts
• And change the planning process for trade promotions

The end result was a more dynamic and effective set of trade promotions.

As we alluded to in the last section, revenue growth management doesn’t work without reorganizing your entire team and reinforcing their roles. There’s a side benefit that doesn’t get talked about here, and that’s making your team more effective in general. Clearly defined roles and responsibilities are positively correlated with job performance and satisfaction, which is a nice tangential benefit as you work towards greater profit.

Using Proper Pricing Models

As a final note, we can’t neglect the role of specific pricing models in general RGM success. This requires deep data analysis and a concrete understanding of general customer behavior and customer behavior by category. Some companies have developed their RGM by modeling pricing strategies in the short and mid-term by channel, region, and SKU. Doing this gives them the ability to simulate different pricing scenarios to adjust their pricing.  With COVID-19 altering behavior in every customer segment, you need pricing models rather than educated guesses.

You may be wondering why, in all the material we’ve provided about the CPG sector, that we’re just creating a piece on revenue growth management now. The main reason for this is that a lot of the previous content that we’ve done ties into this topic in some way. If revenue growth management is the high-concept strategy, a lot of the topics we’ve talked about factor into it. Here are some key examples.

The 4 Most Useful Metrics In CPG Trade Promotion

In this article, we mentioned how many companies have a flawed perception of trade promotion management, summed up with this graphic:

In order to change this mindset, you needed to focus on 4 new metrics:

• Consumer Units
• Revenue
• The Incremental Factor
• Spend Ratio

The whole point of this is to set the stage for your company to do a better job of revenue growth management. Charting the right metrics is key for actually setting your promotions up for success on a larger scale.

What You Need to Know About Doing Packaging Redesign Testing

In this article, we talked about the fact that many companies doing packaging redesign end up blindsided by the negative reception due to their internal testing going in another direction. However, this fails to account for the environment and competitive impact on what people buy. While there’s always going to be a small initial loss due to people not finding your product on the shelf, you need to make sure the redesign draws new people in and then some. 

We laid out a virtual shopping process in this article to test packaging redesigns, and practices like these are an example of the advanced testing and data collection that come when you enter revenue growth management.

4 Ways to Test if Your CPG Sales Baselines Are Accurate

This article mainly covers testing methods to ensure your sales baselines are accurate. While it’s fairly straightforward, the methods here are sort of a prelude to your work with revenue growth management. Like with AI, your work is only as good as your base data. This is why you want to have a data audit workflow well before you talk about any advanced analysis.

Thoughts on The State of Grocery Retail

In this article, we discussed how out of all the major grocery chains, Publix was the clear winner in terms of sales growth, profit growth, and general profitability. This was due to a few major factors:

• Frequent BOGO promotions, as well as implementing BOGO in its marketing
• Focusing on a strong alcohol selection
• Concentrating on brick & mortar over e-commerce
• Perceptions of great customer service and strong perception on perimeter sections

What does any of this have to do with revenue growth management? Publix serves as a great example of what the endgame of smart revenue growth management should be. Using the data they have on hand, they focus on the areas of business that will give them the most profit, like BOGO promotions, brick & mortar sales, and an alcohol selection. This maximizes their store/inventory space as well as their promotional budgets.

Earlier, we mentioned how important it is to have specific pricing models in order to gauge your overall RGM success. This leads to a greater point about RGM in general—how important reliable, actionable data is to any of your measures here. Many of the mistakes we mentioned earlier, in some way, shape or form, are based on poor data. 

As a result, it’s paramount that your CPG business has not only the most advanced programs to help gauge and organize data from your business records but also experts who know how to glean useful insights from them. At the TABS Group, we are the leaders in data-based insight for the CPG segment. Be sure to follow the Resources section on our site for more news and insights on the industry.