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What CPG Companies Can Learn from Netflix About How to Use Analytics

Topics: Analytics, Data Integration, Trade Marketing

When it comes to using the mounds of incoming data to improve performance and increase revenue, Netflix has proven that they know what they're doing. They’ve become so adept at using data to develop and market their product that they can practically guarantee themselves success. In an article featured in The New York Times (“Giving Viewers What They Want”), David Carr outlines how Netflix uses customer data to tailor suggestions and predict which shows to create for individual interests. In other words, they can predict what’s going to work before it ever runs using Big Data.

Wouldn’t it be nice if you could have that predictive confidence with your trade promotion expenditure? CPG companies already are collecting data and with the application of powerful analytics tools such as a Trade Promotion Optimization Solution, they can implement real-time post-event analysis and predictive analytics, thus enabling them to make more educated decisions about what promotions will work before they ever run.

"Adding prescriptive capabilities to your trade program is the culmination of the shift away from tactical guesswork
and toward strategic management of trade investment."

What lessons should CPG companies take from Netflix to make this a reality?

Post-Event Analysis is Key

The first step in taking an intelligent approach to using data is having a post-event analysis process that allows you to quantify the ROI of promotions. With this, companies can assess their current performance at the event level and identify trends that will inform what will work in the future. For instance, “Netflix looks at 30 million “plays” a day, including when you pause, rewind and fast forward, four million ratings by Netflix subscribers, three million searches as well as the time of day when shows are watched and on what devices,” states Carr.

Having this information is crucial to Netflix because it allows them to analyze the behavior of each of their customers and make decisions about what these behaviors tell about how viewers will act. In doing so they create a picture of what effective and ineffective looks like. Similarly, CPG companies can utilize their data to accurately predict the performance of a single trade promotion event or an annual customer promotional plan, so they can begin aligning this intelligence with their corporate strategy.Netflix-Older-Logo.png

The Power of Predictive

Once the intelligence is available, achieving the ability to know what is going to work and when is possible with Predictive Analytics. With capabilities such as predictive what-if scenarios and optimized calendar building that applies predictive modeling to quantify future KPIs, companies can develop accurate optimal plans without resorting to the ineffective guess-and-check method that they currently rely on today.

Taking the Carr article regarding the popular Netflix show “House of Cards” as an example, “Executives at the company knew it would be a hit before anyone shouted ‘action.’” This is because using the knowledge they have from the data of 30 million plays per day, Netflix can predict what will be a hit with customers and build their strategy around opportunities to execute against their learnings.

"With capabilities such as predictive what-if scenarios and optimized calendar building that applies predictive modeling
to quantify future KPIs, companies can develop accurate optimal plans without resorting
to the ineffective guess-and-check method that they currently rely on today."

Chief Communications Officer, Jonathan Friedland, says that “Because we have a direct relationship with consumers, we know what people like to watch and that helps us understand how big the interest is going to be for a given show. It gave us some confidence that we could find an audience for a show like ‘House of Cards.’”

When it comes to CPG companies, they can use the insights from their post-event analysis and then apply this historical data to predict what promotion is going to work in the future. Doing so eliminates much of the risk associated with a tactical change because the data will show how the promotional change will help achieve strategic objectives. This is also true for manufacturers needing to show the benefit of a change from their retail partners' perspective.

Going Beyond Predictive with Prescriptive

But even with the intelligence-driven opportunity with predictive scenario and calendar planning, there remains the “what-if” uncertainty of being unable to consider all of the possibilities available. Applying prescriptive analytics goes beyond manually predicting what will work, to using advanced constraint-based analytics to let the solution run through the various scenarios and promotional mixes available to tell you what the best options is available.

“While careers and entire networks have been made and lost based on the mysterious alchemy of finding a hit, Netflix seems to be making it look easy, or at least making it a product of logic and algorithms as opposed to tradition and instinct,” states Carr.

What this means for CPG companies is that adding prescriptive capabilities to your trade program is the culmination of the shift away from tactical guesswork and toward strategic management of trade investment. With this, companies can adopt an optimization mindset that takes into account a company’s entire promotional performance history and delivers an optimized plan in a matter of minutes, resulting in a quantified return on the #2 line item trade promotion.

Intelligence is a Differentiator

Netflix is a company that is known as being innovative and disruptive; that has successfully thrived in the face of change in the long-established industry of entertainment. Similarly, the CPG industry is very mature and finds change challenging. Adopting an analytical approach to managing trade using a Trade Promotion Optimization Solution is a step that CPG companies can take to maximize their promotional spend, gain a competitive advantage and be disruptive in a mature industry that needs a catalyst.

What to read next: How to Successfully Turn Data Influx into Data Insight with Predictive Analytics


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