Join Kinsa Epidemiologist Maggie Quitter, MPH, to learn how symptomatic illnesses like cough, cold and flu will evolve and rise across the US. Next, we’ll discuss how symptom-relief brands can leverage actionable data to drive sales, improve media campaigns, and keep products on shelves when and where consumers need them.

In this on-demand webinar you’ll learn:

-What’s in store for the rest of the ‘22 illness season and our outlook for the ‘22-23 illness season
-How COVID-19 sub-variants may impact illness and symptom levels
-Epidemiological factors we’re tracking that brands and retailers should know about
-How brands and retailers can use symptom signals to optimize omnichannel media campaigns and avoid out-of-stocks for illness-relieving products.

Kinsa Insights Users have seen:

-40% increase in sales on CRM messaging
-274% increase in traffic using hyper-local illness insights
-50% reduction in forecasting error

Panelist:

Maggie Quitter, MPH – Kinsa Epidemiologist
Brad Pope – Head of Customer Success, Kinsa Insights

With illness continuing to remain unpredictable, marketers for illness-based and symptom-relieving products are challenged to plan and optimize their media spend and target campaigns to the areas where consumers need their products – before they make a purchase. 

Kinsa Insights is the earliest and most accurate predictor of the “when” and “where” for illness-based purchase intent, providing localized, predictive, and real-time illness signals allowing brands and retailers to optimize media campaigns.

Now available on LiveRamp, Kinsa Insights enables users to quickly identify geos with high or trending prevalence of symptoms like cough, cold, flu and allergies, and target ads in these areas to maximize campaign ROAS. Users can choose right-off-the-shelf symptom and illness segment types, like cough, cold and flu, for specific products and objectives, and easily activate them into omni-channel campaigns.

What makes Kinsa Insights’ segments unique?

• Data from millions of households across country via Kinsa health guidance app
• All user data is aggregated & anonymized – no PII
• 200k symptom inputs per day, collected at symptom onset

Kinsa Insights’ proprietary network of over 2.5 million households provides insight at the first sign of illness – weeks earlier than the Centers of Disease Control/ILI network and other claims based data sources. Our five-year historical data base provides predictability into illness and symptom trends down to the zip code level.

Interested in learning more? It’s easy to get started. Let’s discuss how Kinsa Insights integrates with LiveRamp and how it can help brands and agencies with a 4:1 improvement on ROAS. 

At the height of the COVID-19 pandemic, it was a safe bet that almost everyone almost everywhere needed products like hand sanitizer and disinfectants. But now, as we move into what looks like a more regular illness season, how will brands decide where products with illness-based demand, like decongestants and tissues, will be needed and when? With illness data, that’s how!

1. Map Demand by Location

One of the most potent tools illness data can unlock is forecasting where exactly people will become sick. If you’re stuck using historical information, you’ll miss out on the changing and dynamic landscape of illness. But with illness data, you can understand where customers will need your products up to 20 weeks before their illness episode.

2. Reduce Forecasting Error

Forecasting anything, let alone illness, is both a science and an art. No matter how complex the modeling or data is, there is always a chance of something unpredictable. But using illness data, you can reduce forecasting errors by up to 50%. That gives you extra time to adapt your strategies and make sure your product is in front of the people who need it most.

3. Account for Pantry Loading  

An essential aspect of demand planning is understanding what customers already have. You won’t sell much toilet paper if everyone has enough stock for a small army in their closet. Prior to the pandemic, illness products were generally purchased close to when a consumer needed them – but since then, purchase patterns have changed. Consumers are now more likely to “pantry load” and keep multiple products in their homes in advance of when they actually want to consume them, creating inventory in consumer homes. Kinsa Insight’s Illness Forecast can help assess how much product is actually used based on underlying illness levels. 

4. Avoid Out-Of-Stocks:

Illness seasons are volatile. Unexpected surges in demand can outstrip inventory in stores and distribution centers. Out-of-stocks quickly translate into “lost sales” for retailers and impact shopper loyalty. For example, stopping by your go-to store for cold and flu remedies, only to find they’re out, will cause loyal shoppers to shop elsewhere, potentially losing them as a customer altogether. 

5. Plan Ahead

With high accuracy and long lead time, illness data can help your business get and stay ahead of your competitors. You can make sure your products are on the shelf long after other brands have sold out. 

Kinsa Insights is a leading provider of illness data, allowing your company to be the first mover in the illness market. Our illness forecast is the earliest and most accurate, giving you up to 20 weeks lead time. With Kinsa Insights as part of your demand planning strategy, you can stay a step ahead of the competition and keep your products in stock. Interested in learning more? Schedule some time with our team to learn how Kinsa Insights can help you optimize your media targeting strategy and get ahead of flu season before it starts.

As the illness season looms and the delta variant pushes COVID cases higher each day, retailers are hard pressed to make informed plans for the future of products with illness-based demand. During these always-changing times, it’s important to know WHEN and WHERE illness will strike. 

Illness Insights can help companies plan for an uncertain illness season. With early knowledge of when and where illness will occur, retailers can plan media buys and stock shelves ahead of demand. The alternative – stock outs, lost basket sales and a loss in customer loyalty.

Beginning in March each year, Kinsa’s team of data scientists, epidemiologists and doctors create an illness season outlook. They normally look at factors like flu vaccine coverage and rates of global travel. This year, they also take into account things like remote school and work arrangements, mask mandates and levels of international travel. This is all combined with proprietary, localized illness data to create an outlook that predicts when and where illness will rise up to 20-weeks in advance. 

Retailers and marketers with illness insights know what to expect during the upcoming illness season, with enough lead time to take action. They can target media buys to exact geographies weeks before an outbreak begins to build awareness and purchase intent. They can direct product inventory to the right stores ahead of demand to avoid stock outs, drive incremental sales and grow market share. Knowing what you need, when you need it, is the key to success this upcoming illness season.

Kinsa Insights is a leading provider of illness data, allowing your company to be the first mover in the illness market. I’d love to share our latest illness season outlook with you! Drop a comment below or shoot me an email at [email protected] to learn more! 

The pandemic changed everything. How we work, attend school, meet people, and, of course, how we buy things. In 2020, consumer behavior shifted as well. Suddenly, every consumer wanted curb-side pick-up or online purchases delivered right to their homes. As if that disruption wasn’t enough, supply chains buckled and out-of-stocks abounded due to panic-buying and pantry-stocking This led retailers and suppliers to adapt to the new conditions and this shuffle came at a price.

In a normal year, out-of-stocks for all categories of CPG goods cost retailers about $48 billion, according to a report from IHL Group. In 2020, just the top 10 CPG categories totaled more than $2.93 billion in missed sales due to out of stocks, according to NielsenIQ data. More than $800 million was from bath tissue out-of-stocks alone. In the face of these harsh numbers, companies began to look for solutions.

 One of the most prominent solutions seen across many different sectors is a renewed appreciation of how technology can help strengthen supply chains, target ads and predict demand. CPG brands in particular turned to tech solutions, revving up their digital media buys while channeling resources to “buy online and pickup in store” (BOPIS) options for consumers. And, of course, they also turned an eye towards how technology can help create more robust supply chains to prevent out-of-stocks.

In March, The Consumer Brands Association, released a study after analyzing the effect of the pandemic on CPG companies. The CBA called for distributed “supply networks” to become the new normal, askewing the traditionally hyper-efficient supply chains from the before times. These networks, they say, will be built with an underpinning of technology and data. According to the report, “[d]ata is the lifeblood of shaping the future of knowing demand.”

The easiest way to prevent out-of-stocks is to know exactly when and where consumers will want your product. But, according to experts, this hasn’t been the focus for CPG companies. Dr. Kurt Jetta, who has more than 30 years in the CPG and grocery analytics industry, made the observation that a major failure of CPG companies during the pandemic has been a lack of good demand planning. “Over the years, CPG companies have become a bit lackadaisical when it comes to demand planning,” Jetta said. And other industry stalwarts agree. A study from Bain & Company unpacked lessons learned about supply chains during the pandemic. The key takeaway: build resilient supply chains with a focus on improving forecasting accuracy. To do this, the study recommends seeking advanced analytics, which they say can improve supply forecast accuracy by 20-60%.

Kinsa Insights captures unique data the healthcare system misses entirely — data from mildly symptomatic individuals before they go to the doctor, data on how fast an illness spreads in the home or in school, and data from underserved communities that are underinsured, seek care late or not at all. This allows Kinsa to understand emerging illness trends weeks ahead of other systems. 

The ability to accurately forecast demand depends on hyper-local and timely data. Kinsa Insights’ proprietary demand forecasting engine pinpoints where outbreaks are occurring in real time and accurately projects where future outbreaks will occur.

Brands use Kinsa Insights to plan their supply chain down to individual store locations.. Our solution enables brands to drive in-store sales by avoiding out-of-stocks and deploying products where they are needed the most.

Learn how brands saw not only a 50% reduction in forecasting error, by optimizing for illness level and geography,  they also experienced $2 million in additional product demand, a 55% increase in ad engagement, and a 4-to-1 return on incremental ad spend (iROAS).

Contact [email protected] or send me a message to see for yourself how Kinsa Insights helps make unpredictable demand predictable.

Did you know Kinsa Insights real-time illness signals are available in the Trade Desk Data Marketplace?

Illness has never been more unpredictable – making it impossible to predict timing, severity and location of seasonal illness. This has made it challenging for digital marketers and agencies looking to plan and optimize media spend for illness-based brands/retailers.

Kinsa Insights is the earliest and most accurate predictor of the “when” and “where” for illness-based purchase intent, providing localized, predictive, and real-time illness signals allowing brands and retailers to plan media campaigns and budget up to 20-weeks in advance or adjust and optimize in the moment.

Brands and agencies are leveraging Kinsa’s geo-targeted illness insights to:

• Optimize campaign spend to increase ads in areas where illness levels are severe, and decrease spend in areas where it isn’t.
• Enable dynamic creative optimization (DCO) based on illness levels & signals to make sure the right customer is seeing the right message at the right time.
• Execute campaigns that increase brand awareness and grow purchase intent ahead of illness-based demand.

Our proprietary network of over 5-million users provides insight at the first sign of illness – weeks earlier than the Centers of Disease Control/ILI network and other claims based data sources. Our five-year historical data base provides predictability into illness and symptom trends at the DMA, county, and store-level up to 20 weeks in advance.

Interested in learning more? I’d love to show you how Kinsa Insights integrates with the Trade Desk and how it can help brands and agencies with a 4:1 improvement on ROAS! Email me at [email protected] or message me to learn more!