Tough Questions to Answer If You Want Category Captaincy
Retailers expect more than ever from their CPG partners as they face growing shopping challenges, keeping up with consumer demand, and adjusting to ever-evolving trends. If you want the ever-valuable category captaincy, be prepared to answer these questions.
If You Want Category Captaincy, Prepare to Answer These Tough Questions from Retailers
As retailers face growing challenges, keeping up with demand, and adjusting with ever-evolving trends, they’re starting to question the role of their category captains. These people or teams have traditionally assisted retail buying departments, acting as unbiased analysts who worked to deliver the retailer’s goal for the category. Mike Gervasio, President of Category Leadership at PepsiCo and Chairman of the Category Management Association, was quoted in Retail Wire as saying, “It took the pandemic to really shake the behavior of the CPG industry; there’s entirely new problems to be solved.” He said that the industry has been accelerated by 5 years in just a matter of months and that companies have to acquire new sets of data and tools in order to deal with new challenges.
Against the shifting backdrop of consumer behavior, retailers have a real need for a different kind of category captaincy from their CPGs in order to keep them onside. CPG leaders need to prepare for these tough questions from retailers.
Is Your CPG Prepared for These Retailer Questions?
How can we grow the joint profit pool?
Relations between CPGs and their retail partners have fallen to their lowest levels in 5 years according to Bain & Company (2021). However, a well devised joint business plan can deliver more than 10% of incremental profit pool growth for both parties in a single year, helping to strengthen relations.
How can CPGs help us to glean better insights from our mass of data?
Whilst retailers sit on huge amounts of EPOS and loyalty card data, they are not as advanced when it comes to AI, data, and analytics. In return for closer collaboration, there is an opportunity for CPGs to use AI platforms to add value for both parties at a much more granular level to grow the joint profit pool.
How do we get to grips with category management for e-commerce channels?
Retailers are having a tough time adapting to e-commerce, curbside delivery, and marketplaces where category management becomes even more complex. In theory, online sales could give consumers access to endless long-tail choices, but at the same time this creates a logistical nightmare. Retailers need support on how to optimize choices when it comes to assortment and pricing for the online world whilst meeting customer needs.
How can you help us to make assortment adjustments faster and in a more agile way?
Retailers are working to adapt their offers and store formats quickly as the trend toward smaller store formats and neighborhood markets means difficult choices need to be made. How much space should be allocated per category? How can we get the most out of everyinch of that space? Retailers and CPGs need the ability to make assortment decisions in real time. Waiting for annual or bi-annual reviews means potential revenue is leaking away.
How do we ensure the category is managed properly?
When one CPG is the captain of a category in a key retail account, there is always the question of how impartial their recommendations are. AI and machine learning can support CPGs with business case modelling so category decisions are transparent and scientific.
How do we deal with such high levels of product innovation?
Record numbers of product innovations are launched every week. New categories, brand extensions, and even new flavor or fragrance variants mean there’s no shortage of variety. Meanwhile, shelf space is shrinking. Retailers need assistance to model every change made on the shelf to make sure they can maximize revenue.
We how can we localize our assortments at scale?
Over the years, retailers have become better with store clustering and assortment localization. But many want to take their assortments to the next level, delivering even more value to shoppers based on local needs, preferences, cultural differences, and even price elasticity. This is an area where technology can help.
You want to raise your prices, but can you help us understand price elasticity?
One of the biggest tensions between retailers and CPGs is price increases. As a CPG, you face pressures on cost of goods, logistics, and marketing. Meanwhile, retailers want to protect their value proposition and price perception. You can help retailers understand price elasticity down to individual store level using a platform like Insite AI.
Can you help us to develop new store formats and optimize the space?
Spacial optimization is key, especially with increasing smaller store formats where every inch needs to count. Add value for the retailer by helping them understand the spacial elasticity of your products. Prove to them the profit opportunity of allocating additional facings to your SKUs.
Shoppers only buy your products when they are on promotion – Help!
Getting pricing right from the start is crucial. Some products are priced too high, so they tend to only generate volume when on promotion. Likewise, a low everyday price that’s too low means that promotions erode margins even further. Use technology to optimize pricing and understand the demand transfer that happens when prices go up and down. Create appropriate promotional strategies accordingly for the optimal revenue outcome.
How to Win with Optimal Product Assortment
Getting product assortment right isn’t easy, but it’s a major key to success for both brand and retailer. There’s an abundance of data available to support pricing and inventory management, but optimising a store’s assortment is still more often than not based on gut feel and many assumptions. As the brand, shouldn’t you have a significant voice, founded on data, on how retailers are stocking your products?
Customers prefer less cluttered stores, but removing SKUs from them often causes a decline in sales
When stores try to replace lower-selling items, they often find out (too late) that many of the eliminated products are essential to their customers, who then take business elsewhere
Localized assortments that cater to tastes can cause revenue lifts, but trying to apply the same efforts to different categories doesn’t always work
When prices shift from low to high, even with increased quality, sometimes retailers learn the hard way that price matters more
How to identify winners now
It’s not hard to spot and remove poor selling lines using data provided by retailers and 3rd-party sources. But that slow seller could be an essential to your most profitable customers. Simple changes in category and assortment can have a shockwave effect.
For years, CPGs have been using software that promised to optimize the mix of products in a category. But, this technology is largely reliant on historical sales data and is based on manual data inputs. What these systems can’t do is forecast demand for new products, entirely new categories, or account for how shoppers would behave if a particular product were dropped. If you remove one of your SKUs, will demand transfer to another product in your range, or will it be scooped up by a competitor?
The best CPGs work closely with their retailers, adding value through rigorous category management research and recommendation. They can best help retailers by answering questions like:
If slow-selling products are replaced with new ones, what will be the demand for these new SKUs?
If customers don’t find the product they are looking for, will they move to a competitor brand?
How will category sales change depending on the number of products carried?
What is the optimal way to implement store clusters: by customer demand, by geography, by size of store, by store format, or through socioeconomic factors?
For CPG companies, Insite AI can accurately answer these questions, enabling the world’s leading players to maximise the ROI of their R&D, sales, and marketing efforts.
By combining multiple data sources in real time, critical strategic decisions can be made, reducing risk, maximizing revenue, and ensuring value is added for the retailer. Insite AI’s machine learning engine processes millions of data points and combines CPG sales data, retailer EPOS, loyalty data, and 3rd-party sources. It combines this with billions of other data points such as weather forecasts, social media insights, flavor trends, website data, local happenings, and sporting events.
Using this data, Insite AI runs millions of automated what-if experiments, doing what no human category or assortment team could ever accomplish Instantly.
The outcome is accurate predictions and data, down to the most granular level.
You’ll be able to predict sales of brand new products and brand extensions with a high degree of accuracy, right down to the individual store level. You’ll understand the implications of adding or removing a product from a category. You’ll be able to game plan how your competitors will respond. Your CPG will be able to model and test millions of pricing hypotheses, knowing how one change would affect your own brand and those of your competitor.
Together, we can:
Create intelligent assortments
Delight your customers, meeting their demands
Drive brand and category growth
Keep adding more value for the retailer
Forecast accurately so sales opportunities are not missed
Keep you one step ahead of your competitors
Ensure you can take advantage of emerging trends and opportunities early on
If You’re Ready to:
Grow Topline Sales Instantly boost sales by focusing growth strategy on key value items
Improve Efficiency Improve operational efficiency by at least 10% with a low-to-no-touch solution
Optimize Bottom Line Optimize performance of long-tail SKUs by accurately anticipating and responding to demand shifts
Let’s talk! Insite AI will custom-build a solution just for you.