Predicting and Preventing February 2019 Brand & Category - - PowerPoint PPT Presentation
Predicting and Preventing February 2019 Brand & Category Desertion Inmar confidential do not copy, distribute or use without Inmar written permission, 2019 Agenda 1. The Purpose 2. Identify 3. Predict & Profile 4. Activate 5.
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February 2019
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Client formed a partnership with Inmar due to our ability to track actual shopper behavior, understand why it was happening, and then target these shoppers to change behavior, with results that could be measured.
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This new process is a virtuous cycle, can be replicated with almost any consumer segment, feeding learning and optimization
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Activate & Learn
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Identify
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Predict
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Profile
Identify hypotheses for why a key consumer group behaves the way it does. Activate against proven hypotheses to validate findings and hone
Inmar media and
Results feed continual learning. Build a predictive model to identify the key group of shoppers who are most likely to behave a certain way in the future. Profile or disprove hypotheses using basket and social listening data.
Clients can use Inmar data to validate hypotheses, target consumers, and quantifiably demonstrate they can change behavior.
Running multiple models, testing and learning throughout the year translates into the need for a DPN data subscription.
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Attrition Modeling
Category Attritor Category Non Attritor Category Buyers Predictive Model
ML-Boosted Classifier
Predictive Modeling: 1) Identifies in Category Shoppers who are likely to attrite 2) Longitudinal basket analysis allows us to measure shifts purchase behavior 3) Observing lifestyle changes to identify drivers, marketing, and messaging strategies Benefits over Lapsed Buyers methods: 1) Attritors are found early before they exit the category or brand 2) Earlier opportunities for targeted intervention
4 1 2 3Profil
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Inmar built a predictive model that identified future behavior of shoppers with 80% accuracy.
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Inmar used a 273k HH sample from DPN data, spanning 2.5 years and looking at total baskets.
36 key behavioral variables were fed into a model powered by Machine Learning to predict 80% accuracy which shoppers were most likely to leave the category.
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Dollar Trend Flows Show Two Types of Behavior:
Inflows - Start Positive Behaviors vs. Outflows - Ending Negative Behaviors Category attritors mostly exemplify positive behavioral shifts that focus on living a fitness and healthier/heart-healthy lifestyle as achieved by:
Inflows: Starting Positive Behaviors
Attritors are Purchasing More of:
Outflows: Ending Negative Behaviors
Attritors are Purchasing Less of:
vs.
The size of the words represents the magnitude of the index compared to the average 4 1 2 3
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consumption of sweets, breads, and some canned goods in an apparent heart-healthy move away from added sugars, gluten, and sodium.
consumption of lower-fat offerings such as turkey snacks and dry beans as well as imported bottled water.
carbonated beverages are down
attritors are not using these as replacements.
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rise and many of these items are common smoothie ingredients (blueberries, raspberries, sports nutrition powders etc.).
bottled smoothies/juices are on the decline and sports drinks have only a modest increase, suggesting attritors want to mix their own shakes/smoothies for freshness.
market in category products as fresh and flavorful bases high in protein for fruit smoothies/sports shakes.
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completed to create optimal content and consumer targets.
engaging story driven content to change future behavior of consumers most likely to leave the category in the next four months.
engage audiences, educate consumers, and encourage
healthy ingredients, and healthy lifestyle options.
that maximizes the engagement of the campaign via Social Content Ads designed to find the largest number of future category attritors using specific targets of interests and affinities
and measure effectiveness and levels of consumer engagement. 4 1 2
Pred ict
3Profil
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Targeting Capabilities
Interests & Affinities Geographic Demographic Behavior Purchase Retargeting Lookalikes
Instant Hot Pot: Chicken Tortilla Soup
Click the link to see how this delicious recipe comes to life! Start your new year off on the right foot!Curated & specialized Content originates on influencer sites and social channels. Influencer audiences qualified during influencer selection process.
Content reaches primary audiences (friends and followers), and secondary audiences after initial viewers share and engage. (Influencers share)
Inmar selects top-performing content to promote across social channels to targeted audiences. We can target groups based on buying habits, Interests (or the lack thereof) as well as affinities toward your products and drive them to your content All paid distribution drives back to influencer content and/or branded experience pages.
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Pred ict
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From the day-to-day campaign monitoring dashboard…
to custom PrescriptiveIQ™ reports providing valuable insights about your brand and RSLA for measuring return on investment All metrics are measured via first-party tracking pixels and platform API access, and verified by third-party partners for accuracy and legitimacy
In addition to the RSLA, Inmar will provide a sophisticated suite of measurement, analysis and reporting tools
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Difficult decisions suddenly seem simpler. Customer engagement is amplified. Transactions get faster. Costs go down. Sales go up. The possibilities are endless.
IT’S COMMERCE ACCELERATED.
What can we solve for you today?
THANK YOU
www.inmar.com • www.linkedin.com/company/inmar • @InmarInc
Paul Weitzel Paul.Weitzel@inmar.com 847.756.3717 Brent Snyder Brent.Snyder@inmar.com 479.644.1913