When we sit down with consumer packaged goods manufacturers, we learn about their frustrations that led them to seek out a trade promotion management and promotional optimization solution. CPG manufacturers are looking for
- less manual post-event analysis
- a way to quantify promotional ROI
- a more controlled and profitable planning processes
- accurate baselines
The problem🖐 Most CPG companies rely on syndicated baselines to measure promotional performance.
That’s a problem because syndicated baselines are often inaccurate.
• In many cases, syndicated baselines go up dramatically during a promotion – projecting what a loyal consumer would have purchased at full retail.
• This is a great measure to depict pantry load by a loyal consumer, but an extremely inaccurate way to measure the true incremental volume and profit generated by the promotion. In this instance, most promotions would generate no incremental profit due to the increased baseline.
• Syndicated data can be contaminated by various data anomalies that impact the accuracy of a baseline for an inordinate amount of time before being detected by the syndicated supplier or the CPG manufacturer.
A baseline is what the consumer would purchase in the absence of a promotion.
To maintain accurate baselines, CPGs should have a system that identifies data anomalies that contaminate baseline integrity.
Contaminated baselines result in inaccurate post-promotion analysis and future planning. As a result, many trade marketing and sales planning departments approach post-event analysis with skepticism. So many of you plan under the assumption that your baselines are inaccurate and therefore forecasted plans are incorrect. 👎
The cycle of unreliable and ineffective trade promotion tactics goes on…
Why Do We Continue to Rely on Baselines that We Don’t Trust?
In today’s CPG business, there’s greater scrutiny on organizational spend and a strong demand for data-driven competitive strategy. Accepting a “close enough” understanding of promotional performance is a real risk – it puts you at a disadvantage.
Today’s CPG leaders can no longer shrug their shoulders when it comes to quantifying base business. Instead, take control of your data through automation. TPO software harmonizes consumption, spending and shipment data to build baselines that are an accurate reflection of in-store activity.
Blacksmith TPO: Baseline Functionality
We’re looking at a specific account and product group for the past two years:
The dotted line represents the modeled base provided by Blacksmith’s TPO.
The solid dark line imported from your syndicated data shows the difference between data sources.
The new base model (dotted line) provides a smoother and more accurate indication of your base.
This is how a baseline should look – smooth. Not like a roller coaster.
Let’s dig deeper into base volume via the Blacksmith TPO master calendar. The master calendar shows all aspects of how your brand did over a period of time:
Looking at the bottom half of the calendar, we see a week-by-week view of sales and how those sales break out by base and incremental volume – giving us a crystal ball into what portion made up each week and what the driving forces were.
For the most part, our base volume is relatively smooth, but notice the slight increase around the weeks of September 16 and 23.
Only a few instances would cause your base volume to go up or down…
- Regular price increase or decrease
- Increase or decrease in the distribution of an item
- The presence of consumer events such as radio, television, billboard advertising
- Special coupons or demonstrations to draw consumers to try product
(When these instances are present base volume can increase.) If these instances aren’t captured in your data, it leads to questions and an inaccurate assessment of your business.
Now, take a look at the top half of the master calendar. This portion of the calendar shows key information on the same account and timeline selection.
See when consumer events took place. Notice the orange sell for the week of September 16 — it indicates the presence of a consumer event. In this example, a special consumer coupon ran, which drove base volume up at the retail level, even though the specific event wasn’t tied to any kind of specific promotion at this retailer to promote.
With quantified baselines, CPGs aren’t just prioritizing accuracy, they’re emphasizing intelligence.
Using a comprehensive trade promotion optimization solution directly impacts your business in 3 ways:
1) Quantify ROI and KPIs
When you know where you started, calculating how far you’ve come is much easier.
A baseline that builds a holistic picture of your business means calculating the incremental volume, revenue, profit, and ROI of promotional activity is both automated and repeatable across all customers.
2) Analyze Seasonality and New Products
Controlling your baseline-view relative to time periods enables a more thorough post-event analysis during more active, competitive or tenuous times.
For example, a 26-week baseline may be acceptable for mature brands with little volatility. However, a 4-week baseline will indicate more significant shifts during a holiday.
The ability to focus on intricacies through a (trusted) baseline will better inform planning decisions during these times and when launching new products.
3) Usher in the Future
For too long, historical inaccuracies of baseline volume set the foundation for next year’s plans. Today, you can apply predictive analytics to plans for a more definite forecast of promotional lift. These predictive outcomes are built on the actual performance. You can use TPO features to simulate a future baseline based upon current trends, anticipated lost and new distribution. Predictive capabilities provide you with a dynamic future baseline versus (the all too common) static baseline for systematic future planning.
As trade marketers and sales professionals, if you’re ready to ignite change through accurate baselines at your organization, you need the data intelligence to see where you started as a catalyst to create better results.
To date, the elusiveness of accurate baselines has hindered understanding and opportunity. This is why, if the consumer goods industry is going to evolve to address such opportunities presented with shifting retailer demands, rising e-commerce presence, and changing consumer preferences, perceived loyalty cannot be the only underpinning of our business understanding.