Critical Priorities for CPGs to Maximize Omnichannel and Ecommerce Opportunities

Online shopping has seen exponential growth in the past several years, and the COVID-19 pandemic has prompted even more shoppers to look to the safety of the web for their needs. Not only is that online behavior prominent now, but many studies have shown the majority of shoppers who are doing their business online plan to continue, leaving both the CPG and retail industries changed forever. According to Boston Consulting Group, product makers are facing a radically less familiar sales environment as more shoppers turn to ecommerce and even directly to brands. In order to succeed in this transformed landscape, CPGs must nurture emerging capabilities, as well as adopt new strategies and partnerships quickly and effectively.

This means a turning point for CPGs, fundamentally changing the way they reach consumers and maximize wallet share. For many years, the growth of ecommerce could almost be ignored, with reliance on physical retail holding strong. According to BCG analysis, ecommerce only accounted for about 3% of all food and beverage sales before COVID. A small volume by most standards. However, the pandemic accelerated ecommerce to represent as much as 15% of total retail food and beverage sales. Most interestingly, the BCG analysts predict that 70% of CPG sales growth through to 2022 will come from ecommerce. This opportunity will be won by the CPGs with the most agile and sophisticated omnichannel capabilities

Online shopping increased by 50% during the pandemic (Nielsen, 2020) and social commerce grew by 37.9% (eMarketer, 2020).

In addition, the 2021 Food and Health Survey from the International Food Information Council reported that 1 in 3 Americans are shopping for groceries online more often, and that the majority of them intend to continue these habits. 1 in 3 Americans are shopping for groceries online more often, and that the majority of them intend to continue these habits.

BCG analysis reveals that 40% of the recent growth in online grocery is from people trying it for the very first time. By 2022, ecommerce’s share of grocery is expected to be as much as 3 times higher than pre-pandemic levels.

So what can you do to capitalize on these opportunities?

Accurate forecasting
An overarching theme of shopping during the pandemic has been an insufficient available product inventory. Shoppers have experienced their standard, favorite, and even second-favorite products going out of stock – sometimes for months on end. This has led shoppers to trial and shift to alternative brands, and those which have been available when needed have often seen a permanent demand shift. Even during the most normal of times, a CPG’s critical capability is to accurately predict and respond to changes in demand, ensuring stock ends up exactly where the real-time need is, whether online or offline. These predictive analytics abilities allow more inventory to be allocated accordingly, whether it’s by geographic region or channel. Are you going to rely on retailer demand forecasts? Wouldn’t it be better to have these insights available in real time and with both accuracy and granularity?
How do you adapt your marketing and assortments online?
The levers for marketing and promotion are completely different when selling online vs. in store. Instead of allocating shelf facings and space with tactical deployment of in-store gondola ends, power aisles, and POS, you are dealing with digital shelves. CPGs need to deploy strong relationships with ecommerce shops to secure online visibility and placement. Additionally, a focus on which range of SKUs in each category are essential to meet demand is imperative. It’s not always possible for a full range to be stocked, so making quick decisions on the most profitable and in-demand lines can mean the difference between winning business or losing it to a competitor.
Have a deep understanding of the online consumer
Well executed consumer activation is reliant on an understanding of the shopper. How will they find you? When someone searches for your product, how and where will you appear in the search results? Are searches being conducted by brand name? Product name? Category? Will the shopper behave differently when they have instant access to consumer-generated content and reviews from other buyers? Winning in omnichannel is no simple or easy battle: balancing retail, DTC, ecommerce, marketplaces like Amazon, and delivery partners such as Instacart keep CPGs on their toes. The most valuable tool for managing these challenges will make sense of multi-channel data and make smart, go-to-market decisions using it in real time.The good news is that technology has risen to the challenge; platforms boosted by machine learning, artificial intelligence, and data science are enabling CPGs to optimize their operations in real time, making sense of the mind-boggling combination of supply, demand, marketing, promotion, assortment, pricing, and activation metrics.

It’s the brands who can make all these complex, go-to-market decisions faster and with more accuracy that stand to grow and earn the largest share of wallet.

Is It Possible for CPGs and Retailers to Both See Profit Boosts?

Both CPGs and retailers are under immense pressures for different reasons, operating with different objectives. See how a well-built, joint business plan can deliver incremental profit pool growth for both sides.

It is if they work together.

Relations between CPGs and their retail partners have fallen to their lowest level in 5 years, according to a 2021 report by management consultants Bain & Company. According to the firm, the main cause has been a short-sighted approach on both sides that has favored short-term sales targets. CPGs and retailers alike face their share of challenges: CPGs are under immense cost pressure, especially with rising raw materials and logistics costs. Meanwhile, retailers have had to defend their market share against new entrants, such as deep discounters. In addition, the trend toward smaller store formats and the rapid growth of online commerce has further upset the balance. However, according to Bain, a well-devised, joint business plan can deliver more than 10% of incremental profit pool growth for both the brand and retailer in a single year providing they work together intelligently.

The report, which focused on CPGs and retailers in Europe, concluded that only one in four joint annual plans actually manages to create value for both parties, and that instead of building incremental value, 59% of trade promotions merely subsidize baseline sales. They suggest that the traditional, strategic moves from CPGs like launching a new, above-the-line television campaign or new brand extension, are running out of steam and losing effectiveness.

The growing friction between CPGs and retailers is real. In 2016, the UK’s largest grocery retailer, Tesco, delisted nearly all of Unilever’s products after the manufacturer asked for a 10% price increase across its iconic brand portfolio. The CPG’s price increase was blamed on the pound’s fall against the euro and the US dollar. In 2016, Unilever had a 32% share of all the UK’s ice cream and frozen dessert sales, 21% share of all table sauces, and 19% share of butter and margarine sales according to Euromonitor. The disagreement was rapidly resolved, but this example shows what can happen when negotiations fail

The only sustainable solution is to collaborate closely and grow profits together.

According to Bain & Company’s research that was published in 2021, the best CPGs are able to deliver a 10% increase in joint profit pool growth in a single year by doing 5 things differently:

The best CPGs understand both their own and their retailers’ strategies
Getting deep under the skin of the retailer’s P&L enables the CPG to appreciate their business strategy, their most important KPIs, and ultimately how value is delivered to the end consumer. By listening to the other side’s needs and being able to articulate how a CPG initiative will build value is much more likely to get retailers onside.
Deliver up to 20% more incremental sales and profit for both parties through an assortment optimization program
Legacy approaches to store assortment and clustering can lead to high levels of item cannibalization. Limited shelf space often means an ongoing battle between CPG and retailers on which SKUs to stock, how much space to allocate in which stores, and whether a product should be delisted.CPGs had previously been held back without the means to optimize assortments at the lowest, most granular level. However, a cloud-based platform can create optimized assortment decisions at scale, right down to individual store level. This gives clear direction on product mix, space elasticity, and pricing, and a truly optimized assortment has the potential to significantly drive volume and profit for both parties. The latest platforms are able to run millions of what-if scenarios in a matter of seconds, giving real-time insight that allows a proactive assortment approach. The results ensure customers get the value they need, whilst the CPG and the retailer can make the most out of every bit of shelf space.
Take a medium-term view to deliver a business plan
Both CPGs and retailers have monthly, quarterly, and annual revenue and profit targets to hit, as well as shareholders and stakeholders to satisfy. Delivering a successful joint business plan is not a quick fix, and therefore it will take bold leaders who are prepared to invest at least a couple years in order to deliver a properly-executed joint profit plan. As a CPG, you should have a 3-year plan for each of your most important retailers with an imperative of not being distracted by only focusing on monthly sales targets.
Build trust and transparency
Strong relationships are built between people. Beyond the written business plans and agreements, invest in building strong relationships with all the key people within your retail partners. Build these not only with c-suite executives or VPs, but with the people who will actually deliver the day-to-day strategy. This includes category managers, buyers, and shopper marketing directors. Build a real understanding of the KPIs they track. What does success look like to them? How are they being appraised? Then, arm yourself with data that gives them the confidence to buy into your CPG’s initiatives, whether it’s store assortment, a new range, or a price change. If you’ve got granular data to prove something, then you’re halfway there.
Break down silos within your CPG
Most CPGs have teams dedicated to their most important retailers to bring people together from commercial, category, sales, marketing, manufacturing, and logistics.Whilst people from these disciplines do work together on projects, it is incredibly challenging to avoid a siloed mentality. There are many widely-cited solutions to the siloing issue, and hundreds of management books have been written about it. However, taking a pragmatic approach to ensure teams are collectively responsible for delivering the retailer’s P&L with common goals and objectives is the key. Ensure the collective responsibility is mandated from the highest level of leadership within your CPG so it has a real sense of purpose and gravitas.

There’s a New Growth Engine for CPGs

How AI Is the New Growth Engine for CPG Chief Growth Officers

Executives at the world’s leading CPGs have huge amounts of data and insights available to them, and with R&D centers around the globe and huge insight budgets at their fingertips, some might argue that the role of the Chief Growth Officer would be an easy one. But the reality is that, despite their extensive corporate resources, agile startups are nipping at the heels of large product manufacturers and the sheer size and complexity of CPGs doesn’t always work in their favor. The huge amount of data and insights coming in from the market is creating analysis paralysis – a situation where multiple feeds of static data are sitting in silos in different parts of the organization and delaying crucial strategic decisions.

It’s never been a more challenging time to be a Chief Revenue or Growth Officer. To survive and thrive in the increasingly challenging economic environment, brands and retailers need to collaborate closer than ever before to put the customer at the center of their business decisions. Yet in practice, retailers are highly protective of their consumer data and rarely share their real strategic agenda with their suppliers. With dramatically and quickly shifting consumer tastes, preferences, and shopping behaviors, as well as own-label powerhouses like ALDI and Trader Joe’s, many factors are gradually luring people away from branded products.

Multiple pressures are on the Chief Growth Officer: colleague and shareholder pressures, shorter product innovation cycles, retailer and consumer demand for fresh items more frequently, and a vicious grab for market share in new and interesting categories.

There is also a paradox within modern CPGs: they want to act agile in order to compete with the new string of direct-to-consumer innovators, but these startups are often funded by bullish venture capitalists willing to take a risk across multiple bets. Yet CPGs must be prudent and are typically risk-averse. So how can you act agile if you’re not willing to take a test-and-learn approach?

AI and machine learning hold the key to making agile innovation less risky and can make predictions with unbelievable accuracy. Solutions like Insite AI sit within your own cloud, securely bringing together millions of data points from inside and outside the business. Historical sales data, category data, consumer insight data, 3rd-party data from the leading research houses such as Nielsen and Kantar…add to that unstructured data such as the latest trends reports and insights from countless social media posts where consumers share their emerging behaviors, ideas, opinions, shopping trends, and future intent.

As a leader responsible for growth and revenue, you need to combine millions of disparate data points and connect the dots between things that would be impossible for any team of people to achieve. This is where AI and ML come in. Imagine a world where millions of scenarios are created in hours (not days or months), with a result of clear intelligence on categories and product concepts with highly accurate and granular forecasts of how they will perform in each channel (retail, e-commerce, direct to consumer) and at different price points. Just imagine the step change in your organization when you can sift through your innovation pipeline and have the confidence to commercialize projects, removing the nagging doubt of failure.

If you’re ready to see how Insite AI’s proven engine will drive incremental growth, customer-market fit, and added value for your retail and distribution partners, then you’re ready to turn the uncertainty of rapid change into your CPG’s opportunity.

Could AI Have Predicted the Explosive Growth of Hard Seltzers?

Hard seltzers have seen sparkling growth over the last few years, and really took hold of the alcoholic beverage scene in 2019 and 2020.

In a recent Nielsen study looking at March and April in 2020 vs. the same months in 2019, consumers decreased their share of spending on beer and wine, with beer losing 5.6 share points and wine losing 4 share points, and these spending shares show even more discrepancy in hot-weather seasons.

Mainstream beer and alcohol manufacturers who have taken on hard seltzer production represented less than 20% of the market as of June 2020, meaning that those brewers missed out on getting a piece of the action earlier and have forfeited a larger market share.

The hard seltzer segment has caught the attention of brands around the world, and they’re all eager to grab a slice of this growing market. At the beginning of 2018, just 10 brands were on the market; by the beginning of 2019, there were 26 hard seltzer brands and right now, there are more than 65 brands fighting for consumer attention:

During and early summer of 2020, hard seltzer off-premise sales in the US (i.e. supermarket and convenience store sales) quadrupled on a year-on-year basis, and showed an increase of $900 million.

Consumers now have choices that include traditional hard seltzers, cider seltzers, wine seltzers, spritzers, spirit-based seltzers, and the list goes on. There’s no shortage of options in this category.

Many CPG brands faced both c-suite and shareholder backlash for not predicting or at more quickly reacting to this global trend. Some brands have come late to the party and have been forced to play catch-up, having to forge new brands from scratch or find meaningful ways to add extensions to existing brands (a reaction seen from some of the well-known beer brands).

Retailers now have dozens of seltzer brands all fighting for.

Many CPGs saw the shift happening before them, but didn’t act sooner because they just didn’t have an accurate way to predict the potential sales or profitability of such a launch. The largest drinks companies won’t give a new brand the green light unless they can guarantee hundreds of millions of dollars in sales right off the bat. In the USA, the market is dominated by White Claw and Truly. White Claw was the brainchild of Mark Anthony Brands, the creator of Mike’s Hard Lemonade. Truly was created by the Boston Beer Company, maker of Samuel Adams. Unbelievably, the Boston Beer Company now sells more hard seltzer than it does beer!

So how could other beverage brands have spotted and acted on this trend earlier, securing a larger market share?

The problem with many beverage companies and CPGs is that data is siloed across many places: trend forecasts from strategic consultancies and futurists; shopper data from retailers (which typically is owned and guarded by the retailer); the company’s own sales and category data.

Trends like the hard-seltzer phenomenon could have been spotted much earlier by tuning in to the weak signals coming from the market. Often these weak signals are too faint for any one department to spot.

Social media, blogs, and even restaurant menus are another source of insight – the problem is, there’s such a huge mountain of data, any R&D or insights team would need to trawl through millions or even billions of data points to spot emerging trends.

It’s just not feasible for humans to do, and siloed data is too challenging, time consuming, and cumbersome to analyze, respond, and act quickly.

This is where an integrated AI platform shines. Insite AI will analyze feeds from multiple sources, joining the dots between data that would normally never be combined. It ingests internal sales and performance data, market-share metrics, and much more, then runs simulations and forecasts, combining it with data from the likes of Nielsen and Kantar and EPOS data from retailers. The AI engine has the ability to trawl through billions of social media posts and articles, too, turning this raw and disparate data into intelligence. Combining this intelligence with billions of what-if scenarios, you’ll be presented with decisions on which you can be confident, giving the CPG rigorous ammunition to prove your business case to both your company and your retail partners.

Intelligent decisions, founded on data.

Had some of the world’s largest beverage brands used this technique, they would have spotted and accurately predicted the performance of the hard-seltzer category. They would have moved faster, created new brands more quickly, and entered the market much earlier, gaining greater market share and consumer mindshare. Not only that, they would have been able to prepare their logistics and manufacturing infrastructure, ready for the huge bottling volumes required to fulfil demand.

This hard-seltzer tale is not entirely unique, and it won’t be the last. Other categories are also about to explode. Trends and changes in consumer behaviour are bubbling away.

As a CPG, imagine the gains to be had if you could anticipate now and reap the benefits of being ahead of the curve later.

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.

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3 Ways CPGs Use AI to Increase ROI

Every CPG strives to maximize its return on the money and effort it places into investments. The question is:

Which parts of these investments will drive the biggest and most certain returns?

Optimized category management, assortment planning, and revenue growth management are the key factors to success, profits, and market share.

Don’t take chances on your success – using artificial intelligence to make decisions ensures optimal outcomes. Here’s how CPGs are using it:

1. Category Management

Spend precious technology and data dollars on the product most likely to help you succeed. This means using a solution that continually monitors and uses data to create all outcome scenarios possible.

These scenarios use past, present, and future-possible data to show you and your retail partners which products should be on shelves and at what price.

Key benefits of AI-driven forecasting in category and assortment:

Selling the right quantity of product that accounts for upcoming sales, trends, advantage over competitors, and promotions
Better optimization of assortment ratios
Improved understanding of demand drivers and customer behavior, right down to the SKU level
Decreased lost sales / missed sales opportunities
Better alignment between products and locations where demand exists
Improved GMROI

An AI-based forecasting system, is a focused on the CPG major upgrade to existing systems where brands attempt to manually cluster and define data and patterns. Unsurprisingly, results are often disappointing and lead to lost sales and market share.

Store-level forecasting is a difficult endeavour with traditional systems, especially when CPGs are dealing with millions of possible product, price, and store combinations.

By alleviating the need for so much manual intervention and by accounting for so much information at any given time, artificial intelligence-based forecasting can deliver far more accurate decisions.

2. Revenue Growth Management

Advanced forecasting combines with historic sales with seasonality, trends, product lifecycle effects, and statistically-tested assumptions to improve accuracy. Increased accuracy is the single biggest driver of direct savings, revenue, and total return on
investment. Improvements to revenue growth management will be realised in the following ways:

Customized decisions for granular levels such as individual store, SKU, particular time, price elasticity, and demand changes
Making optimal pricing decisions to make you more money and take market share away from your competitors
Opportunity for improved use of strategic discounting

3. Operational Efficiency

In the face of increasing competition, CPGs are all looking to ensure their products remain a focus over their competitors, and that their retail accounts keep them top of mind.

More accurate simulations for decisions can help CPGs optimize category, assortment, trade fund, and pricing/promotion. This is while ensuring they’re able to offer retailer partners the right discounts and provide exact pricing recommendations for optimal outcomes on either side. It’s important that assortment is accurate at individual store levels, using both micro and macro views for trends, seasons, demand, and changes to ensure customer demands are being served at a granular level. Product imbalances often occur right after seasonal peaks. One of the biggest reasons CPGs fall into this trap is because they’re often forced to act retroactively with top-up orders, transfers, or pricing changes. Providers such as Insite AI provide highly accurate, data-driven scenario decisions at store levels ahead of time to keep ahead of competitors.