How Unilever is driving growth opportunities with RM

FMCG revenue professionals face a tough balancing act. They need to offer consumers the right product at the right price, create value with retail customers in challenging times, and deliver both top‑ and bottom‑line growth. All of this must happen within strict legal limits, including regulations that prohibit resale price maintenance.

To manage this complexity, leading consumer goods companies such as Unilever rely on revenue management (RM). RM provides a structured, data‑driven way to make better pricing and portfolio decisions. In practice, it helps companies protect value and identify growth opportunities, even when markets are under pressure.

Many revenue professionals recognise the value of RM in theory. The question is how it works in practice. How does an RM mindset translate into day‑to‑day brand decisions? And how can it help teams respond to sudden changes, such as rising costs or intense promotional pressure?

In this article, Chi Wai Tang, RM Country Lead for Unilever in 2020, shares his first‑hand experience of applying RM to two leading Dutch brands: Unox and Andrélon. He explains how Unilever puts RM into action — and what other brands can learn from this approach.

Ushering in an RM mindset to unlock growth potential

Chi Wai Tang joined Unilever as Senior Deployment Manager for Revenue Management in Europe. For him, revenue management (RM) is not a one‑off project or a single tool. He sees it as a disciplined way of working.

“RM is a journey,” Chi Wai explains. “You start by setting clear goals and really understanding the root cause of a problem. That’s what helps teams think differently. It also means looking at a revenue management challenge from several angles and asking better questions.”

At Unilever, RM combines insights from different data sources, both internal and external. These insights are analysed and visualised to build a clear picture of what is happening in the market. This helps teams make informed plans, review decisions, and adjust their approach over time.

Today, Chi Wai works closely with Unilever’s Dutch brand teams as the Netherlands RM Lead, based at the local headquarters. At a time when raw material costs are rising and market growth is slowing, his focus is clear: using RM to support price growth and protect market share.

“RM has created more transparency in trade investments and our ‘five-lever analytics’ have identified pricing opportunities,” he said. These levers include: portfolio, pack price, mix and distribution, promotional strategy, and trade terms (i.e. contracts).”

To apply these levers effectively, strong data analytics are essential. This is where SKIM is often brought in. We developed an RM Framework that helps break down product, portfolio, and pricing decisions using the five‑lever approach.

The framework makes a clear distinction between internal levers, such as brand, pack, and price, and external levers, such as channel dynamics and trade term conditions. This structure helps teams see the full picture and understand how different decisions interact.

By working with both internal and external levers, we tailor each project to the client’s situation. This allows our clients to make more informed and holistic pricing decisions, grounded in data and real market dynamics.

Analytics approach for successful RM strategies

In today’s data‑rich environment, a successful revenue management (RM) strategy needs to be data‑driven. Revenue management professionals like Chi Wai increasingly use a wide range of data sources. These include segmentation data, brand trackers, historical sales data, and consumer insights on price sensitivity.

When you recommend a price change or review your portfolio, it is critical to understand how consumers are likely to respond. The quality of revenue and share forecasts depends heavily on the research methods used and the strength of the underlying analytics.

Historical sales data can provide useful context, but it is not enough on its own. Past behavior does not always predict future decisions. As Chi Wai points out, consumer lifestyles and shopping environments are constantly changing. That is why robust analytics, designed to predict consumer choices, are essential for making strong and credible pricing recommendations to retailers today.

To support these decisions, SKIM uses discrete choice modelling (conjoint analysis) to test pricing strategies before they are implemented. With more than 40 years of experience in choice modelling, this approach is a core part of how we support revenue management decisions.

Chi Wai, who has over a decade of experience in revenue management, strongly values this method. He describes the conjoint approach as “the best of the best.”

He adds, “from an RM perspective, your research needs to simulate realistic shopping trips – from the shopper type and channel, to promotions and competition – and calibrate with market and financial data into a robust prediction model. That’s what SKIM does best.

When I was at Imperial Tobacco (2015), we led a global tender where SKIM came out as best in accuracy versus costs.”

RM in action: two Unilever brands, two challenges

How does Chi Wai put his RM vision into practice at Unilever?

Two recent projects clearly show how FMCG brands can turn a revenue management approach into real business decisions. In both cases, Chi Wai worked with Dutch brand teams that faced important questions about how to adapt to changing market conditions.

Unox covers a wide range of food products, including smoked sausage (rookworst), soups, and noodles. With an 80‑year history, it is Unilever’s most valuable brand in the Netherlands. When pork prices increased due to the Asian swine flu, the team needed to explore pricing options carefully. Using RM’s structured analysis approach, Unilever developed and tested different solutions with the conjoint model.

Andrélon is the best‑selling hair care brand in the Netherlands, offering a broad range of shampoos, conditioners, and styling products. The challenge here was different. Unilever wanted to continue growing market share, even though Andrélon was already the category leader. This was made more complex by a market with nearly 93% of sales under promotion at any given time.

Working from the five‑lever analytics approach to revenue management (RM), Chi Wai shared market and customer segmentation data, promotional details, and channel preferences for both brands. Using these inputs, our team designed two virtual shelf studies to assess the impact of potential price and pack size changes and to identify the best portfolio options for Unilever.

In these studies, consumers were shown a digital retail shelf with different brands, prices, and pack sizes, closely reflecting the in‑store experience. This allowed us to observe the trade‑offs shoppers made when choosing between options. For Unox alone, the analysis covered ten different shopper types.

The objective of both studies was clear: to deliver strong pricing and portfolio insights for the Unox and Andrélon brand teams, as well as for their retail partners. As Chi Wai explains, “We needed to make a convincing case to retailers who were under pressure in a challenging market.”

So what were the results?

At the end of each study, Chi Wai received the SKIM simulator tool. This tool predicted shopper behaviour across different segments and scenarios and showed the expected impact of price or pack size changes on volume and revenue.

For Unox, Chi Wai says he trusted SKIM’s approach as “the most accurate available today.” For Andrélon, the key focus was understanding the impact of heavy promotional pressure on shopper behaviour.

“Incorporating promotions into a virtual shelf model is challenging,” Chi Wai explains. “But SKIM had a strong approach.”

For Andrélon, this meant building a robust pricing model using SKIM’s proprietary algorithms. The model also predicted how promotions influence consumer behaviour, helping the team understand the real impact of promotional pressure on pricing and choice.

According to Chi Wai, the results helped Unilever’s trade teams present “a strong value-add that showcased them as category captains in this field.”

Revenue management (RM) and the work with SKIM helped Unilever strengthen its conversations with retailers. The teams were able to support their recommendations with clear, fact‑based insights, such as price elasticity, and keep the discussion focused on the consumer’s wallet. Retailer feedback was very positive.

Expert advice: How to get started with RM

At Unilever, Chi Wai aims to create a culture of radical open‑mindedness and transparency. He believes this is essential for fast learning and meaningful change. When asked how other revenue and pricing professionals can start adopting an RM mindset, he shares the following advice:

• Be courageous and commit to revenue management
  
  
• Start small if needed — even adding one extra data source can improve your next pricing decision
  
  
• Expect some initial discomfort when asking tough questions; that’s where growth begins
  
  
• Don’t avoid the rigorous process — “in for a penny, in for a pound” is what delivers results
  
  
• Pay attention to how you communicate your insights

Many revenue professionals are strong with numbers, but emotion also plays a role. Keep the message simple and support it with evidence to build credibility.

---

If you’d like to learn how SKIM can help you build a strong pricing strategy and get started with revenue management, we’d be happy to talk.