How Analytics Helps Fast Moving Consumer Goods Move Fast!
Over the last decade, the fast-moving consumer goods (FMCG) industry has experienced healthy growth. One of the reasons behind the growth was the adoption of experience retailing along with a general shift in consumer preference towards enhanced shopping experiences. The trends in the FMCG sector change constantly due to dynamic consumer behavior. This puts FMCG companies under great pressure as they need to adopt an agile operating model.
Some of the common challenges the industry faces are –
- Fluctuating demand
- Flexible pricing needs
- Portfolio expansion decisions
- Fickle customer loyalty
- Management of multifaceted supply chain
- Difficulty of integrated planning
But many leading FMCG companies have started making use of technology to beat these challenges and build on emerging opportunities in this evolving marketplace.
FMCG companies have started adopting advanced data-driven analytics tools to reduce their vulnerability to the impact of constantly changing consumer trends.
Advanced data analytics solutions can offer the FMCG companies the ability to profile, segment, and analyze customer data to better understand purchase trends, price sensitivities, and much more. The effective usage of analytics can help FMCG companies stay ahead of the competitors and maximize the benefit from emerging trends in the FMCG sector.
Let’s look at the role analytics can play in making Fast Moving Consumer Goods move fast.
Providing deeper customer insights
To improve promotion effectiveness and make them customer-focused, FMCG organizations need to better understand changing customer preferences. This is essential to create personalized messaging and options.
Through qualitative and quantitative marketing research approaches, companies can get data on how their customers behave. Analytics can help them understand customers’ experiences and figure out ways to drive customer loyalty.
By using advanced data analytics, FMCG firms can get actionable insights into customers that can help them uncover promising sources of growth and develop successful product options. They can use these insights to create effective marketing campaigns and strategies for-
- Segmentation
- Branding
- Product design
- Pricing
- Customer experiences
- Effective value propositions
Increasing profitability
In the last few years, like other industries, the FMCG companies have started collecting an impressive amount of data on their customers’ purchase behavior, items purchased, place of transaction, choices, etc.
By making effective use of all this collected data, FMCG firms can increase profitability through strategic decision making. As per a study by the University of Texas, businesses can increase their revenue by $2 billion a year by increasing data usage by just 10%.
Some of the common benefits of analytics in increasing profitability are-
- Insights from data analytics can help create impactful and cost-effective marketing, thus increasing profits.
- Analytics can help FMCG firms improve product value propositions and personalize price points for better outcomes.
- It can help companies cut costs on products that are under-Performing and focus on products that drive more revenue and profits.
- By moving quicker than competitors, businesses can deliver timely solutions to customers faster than competitors.
- Data can drive much better planning and budgeting, thus reducing wastage of resources.
- Analytics can provide accurate sales forecasting and predict sales volumes based on critical demand drivers.
Developing a pricing strategy
Data analytics can help FMCG firms optimally price their products for different customer segments. Using analytics, brands can leverage demand variation at different price levels with different promotional offers. This will help them get the maximum value out of their product offerings while still ensuring sales uptake. This can further increase the sales margin and decrease markdown.
Sentiment analysis
Using analytics-powered web crawlers, companies can capture feedback from customers across social media platforms and derive meaningful and actionable conclusions. Text mining models can help parse online conversations into positive, negative, or neutral messages to drive responses.
Sentiment analysis backed by advanced analytics can help companies track consumer behavior in real-time across various channels, monitor brand health, and uncover factors that can impact the business.
Inventory optimization
With data analytics, brands can align inventory planning, forecasting, and logistics capabilities and decisions. FMCG firms can employ statistical modeling techniques to analyze inventory stock levels and develop robust demand forecasts through statistical analysis of data.
The suggested order quantity recommendations offered by the analysis can reduce the instances of out-of-stock inventories as well as over-stocking. This allows optimal inventory levels across locations based on all supply and demand variables.
Advertising analytics for driving sales
Companies can gain a lot if they can figure out which combination of ad exposures can influence customers to make a purchase. Analytics proves beneficial in this regard. It helps measure how TV, print, radio, and online ads function to drive sales. Based on this understanding of appropriate media mixes companies can better allocate marketing spend. They can also figure out if the company is investing the right amount at the right point in the customer decision journey.
Other benefits
Some of the other benefits of analytics in the FMCG sector are –
- Identification of lost opportunities.
- Understanding the company’s market share and competitor performance.
- Figuring out the ROI of the company’s marketing strategy.
- Analyzing the performance of new products.
- Identification of new segments to target.
- Spend analysis.
Conclusion
The digitalization of retail has shifted the needle from a product-centric to a customer-centric approach. For the FMCG sector, this is a strong signal for the use of analytics. To move fast in the world of fast-changing consumer demand, companies need to pay attention to collecting data, turning it into insights, and optimizing actions.
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