CPG data analytics address product, pricing and customer behaviors. According to Accenture, only 9% of businesses have fully implemented an analytics operating model.
Data-driven. Analytically-informed. Advanced customer analytics. Strategic intelligence.
These catch phrases line job postings and board rooms at leading CPG companies. The emphasis on being analytically savvy has pivoted from having analytical capabilities – turning available data into usable information – to being analytically excellent – acting on this information for accurate intelligence, strategic decision making, and predictable revenue management. Everyone is looking for a way to navigate the competitive landscape and plan better promotional investments. CPGs leveraging data analytics focus on calculable revenue growth.
This analytical transition has created 3 expectations of growth focused CPG leaders:
1) Demand for Accuracy
According to the Consumer Goods Technology State of Trade Promotion Management report, “Not a single respondent indicated that they are completely satisfied with the quality performance of their analytics.” This troubling revelation infers that we must improve the analytics processes and data quality used for modeling, interpretation and outcome forecasting.
In the area of trade promotion, there is significant opportunity, with the integration of a trade promotion optimization (TPO) solution, to eliminate hands-on data compilation and modeling in favor of automated harmonization, baseline smoothing, lift-curve generation, and predictive modeling.
TPO standardizes the process and builds the foundation for accurate and timely analysis.
2) Analytics to Drive Action
Gartner’s predictions – that 60% of CMOs will cut their marketing analytics departments by 50% by 2023, due to a ‘failure to realize promised improvements’ – are in line with a recent Kantar study that shows that marketers are having trouble determining marketing performance and missing opportunities for growth.
This means that it’s not enough to just calculate KPIs. We have to combine these metrics with predictive capabilities that allow us to see how we act to improve the outcome.
For example, how do you determine the impact of making one change to one promotion for one customer? If we can’t apply our analytical insight to build a detailed and definite answer to this question, then our analytics will continue to be a snapshot of the past that we use justify poor investments.
Use the predictive analytical capabilities of a TPO application to model test scenarios or promotional combinations and the constraint-based modeling functionality to optimize outcomes aligned with business objectives – shifting CPGs from passive observers to action drivers.
3) Understand and Evaluate the Dynamic Relationships to Impact Outcomes
An Accenture study reports that only 9% of businesses have made predictive analytics a priority, focusing instead on hindsight descriptions of what has already occurred. The benefits of artificial intelligence [AI] include the ability to continually update new data that reflects changing conditions. With AI technology, it’s easier to explain how a decision or recommendation is made since the tool captures cause-and-effect relationships. For CPGs, this means that we must be agile with our understanding of the business and provide comparative visualizations as to see the relationship between data and decisions.
Trade promotion optimization puts the ability to understand and forecast at our fingertips. Machine learning capabilities immediately account for trend fluctuations and anticipated disruptions. The opportunity to then compare the current state to other iterations supports an analytical process of decision making aligned with organizational priorities.
These evolving expectations of CPG leaders raise the bar for analytics. For organizations to build and execute growth opportunities, they need CPG data analysis via trade optimization software, which requires letting go of the manual processes. TPO data will open the door for validation of analytical intelligence and shape an analytically-driven growth strategy.