Category Archives: Analytics

How does a new emerging product target effectively find its audience?

MMI Brands is in a strategic alliance with IRI, a global leader in syndicated sales data and market research, to develop new and emerging brands introduction initiatives.

Robert Berg has been working in the CPG industry for more than 25 years. After earning an MBA from The Wharton School, Robert began his career at Coopers & Lybrand Consulting and PriceWaterhouse-Coopers Consulting. Working for IBM Global Business Services, Robert worked on one of the largest CPG mergers in 2001. During his 13-year tenure with IRI, Robert has focused on rolling out new solutions for both CPG manufacturers and retailers and is currently working with mid-market clients.  He is also charged with helping IRI clients receive the greatest value from their investment in IRI’s consumer and shopper solutions.

 

  1. Previously we talked about focusing on the right shoppers and right retailers. You provided more details on how you target the right retailers. Let’s talk about targeting the right shoppers and let’s take a tough example. One of the challenges of a new emerging product is that there is not a lot of information on the product buyers. How does a new emerging product target effectively find its audience?

 

That’s a really important point and I appreciate you raising it. Companies want to find the buyers who will buy more of their product and find them efficiently. Finding the right audience drives faster re-order and validation. Getting the first order and expanding distribution is really exciting. Getting the first re-order is just as exciting. The faster we find a product’s initial audience, the more efficient the whole company’s operation becomes.

 

How do we effectively find these buyers? The greatest predictor of future purchasing is past purchasing. However, when you don’t have past purchasing history, what can we use? We use product attributes. The capability is available to target buyers of the collection of attributes. What we do is help companies compile a group of existing products that have the attributes of the new product. These attributes can be natural/organic quality, ancient grains, weight loss, vitamin-enhanced, size, format, packaging, etc.

 

We aggregate the buyers of these attributes and find household clusters that buy the collection of the attributes. This is the starting point of who the buyers are. As the product builds and engages with more buyers, we will see additional households that the product resonates with.

 

The value of the initial target buyers is to focus the resources of the company in those locations and play bigger in locations that mean more to the product success.

 

  1. What is unique about this approach?

 

There are a number of propriety things in this approach. Briefly, it’s an accessible, purchasing-based solution for creating and crafting targets to new emerging products. Getting this type of information quickly and accurately was something only large manufacturers and retailers had access to. IRI offers the ability to associate the purchases of products to households. This allows us to find the households that have a high propensity for the collection of products with certain attributes. IRI has made this process fast, accurate and accessible. The target is created in a few days with the ability to then contact actual households for activation, geographies and retailers for prioritizing resources.

 

  1. What data do you use?

 

We blend a few databases together. IRI has access to a panel of more than 100,000 people, who track their purchasing and consumption. This is how we identify the households who are purchasing particular products.   There are other datasets we use, such as Experian’s ConsumerView a database with 126 million U.S. households; Experian’s Mosaic, which is Experian’s proprietary lifestyle segmentation; and Simmon’s National Consumer Panel, a database for media and psychographic insights.  There are other databases and methodologies we use; however, these are the most visible ones.

 

  1. How does someone use this to reach the right audience?

 

There are two ways to reach your target audience. One is directly to the consumer and the second is through the retailer. The direct to consumer contact strategy is enabled through IRI’s relationship with Experian.  Once we have created a target, we can send to Experian. Through Experian, we can also get mailing addresses, email addresses or telephone numbers.  Here a two examples.

A food client used a mailing list of all the target households shopping at a retailer. They mailed this set of households a colorful flier. Before the mailing, 38% of the converted shoppers spend on this category were purchased at the retailer. After the campaign, 43% of the converted shoppers spend was on this category in this store with more on the company’s product.   This is an indication that a sharper focus on current shoppers at a retailer can influence and improve performance.

A health and beauty client used a target to focus on the right buyer and right locations for this product. This move made a big impact, because the client understood where NOT to focus and eliminated 25% of the stores that were low fit and low potential. The client went forward with a digital campaign at 75% of the cost and achieved close to 100% of their goals. The savings dropped to their bottom line.

This is the strategy of relative strength: invest in the consumers or in the stores which have a higher propensity to be a valued, long-term investment. The opposite side to this strategy is to eliminate spend on consumers and stores with a low return on investment.

 

      5.  Is this useful more for marketing or for sales?

 

Both marketing and sales can use this information – they use different elements very differently. Good marketers really know how to leverage this data to inform their marketing planning. Good sales people need to know at which retailers to engage these consumers and use it for a compelling story about these shoppers to the retailer.

It’s important to transfer the information in a way that’s useful. Many times, this data is provided as a data dump and there is a disconnect between having the data and using it productively. It’s important to quickly find your story and highlight the facts each audience needs to understand.

 

      6.  What is the value proposition for something like this?

 

The minimum one should be able to recoup from this information is to eliminate the 25% lowest ROI consumers or retailers from their plans. Eliminate the marketing and sales expenditures on areas with high concentration of low potential consumers.  It’s a straight cost saving and falls right to the bottom line.

Finding your product’s audience and then planning your marketing and sales more effectively can be worth a lot of money. To get a higher return from your marketing and sales, it is important to craft a target based on the needs of the company and the near-term activation. You may want to isolate younger households or households that are more responsive to digital media. Those are modifications that can be made to the target to ensure that the group is more focused and resources can be deployed with more effective and efficient results.

 

Let us show you how we could help your companies’ brands

MMI Brands is in a strategic alliance with IRI, a global leader in syndicated sales data and market research, to develop new and emerging brands introduction initiatives.

Robert Berg has been working in the CPG industry for more than 25 years. After earning an MBA from The Wharton School, Robert began his career at Coopers & Lybrand Consulting and PriceWaterhouseCoopers Consulting. Working for IBM Global Business Services, Robert worked on one of the largest CPG mergers in 2001. During his 13-year tenure with IRI, Robert has focused on rolling out new solutions for both CPG manufacturers and retailers and is currently working with mid-market clients. He is also charged with helping IRI clients receive the greatest value from their investment in IRI’s consumer and shopper solutions.

  1. We have gotten a lot of responses from your last interview from people who want to get into more specifics concerning store-level insights. They want to see some specifics. Would you be able to share an example?

Absolutely, I would be happy to. Previously, I discussed two questions concerning retailer insights, which we can take to the store-level.  Those two questions were:

  1. At which retailers or stores do they shop at higher concentration (even if your products are not offered there currently) or how important is your shopper to the retailer’s sales?
  2. At which retailers do you have a reasonable opportunity to make the most money this year?

Allow me to explain this with a picture of the measures and a graphic on the results. For the first question, we calculate how much each household (HH) spends at a retailer and then sum the share of wallet of those HH’s we identified as the target.

In this example, we created a target for a new emerging product and generated this information at the banner level. (I’ll show store level in the next example.) We are going to see where are my shopper’s spending their money in higher concentration and how important are they to the retailer?

How do you read this chart? Let me give you the definition of all the measures and then we can discuss.

Total Estimated All Commodity Volume (ACV) (MM) is the sales (of the items IRI tracks) of that store.  This measure gives one a sense of the size of the retailer or store.

Target ACV (MM) is how much of the retailer’s total estimated all-commodity volume (ACV) is accounted by our target shoppers.

Target % ACV is (Target ACV/ Total Estimated ACV) is the percentage of the total retailer ACV$ our target shopper accounts for.

Target % ACV Index is (Target % ACV/ Average Target % ACV) indicates whether our target % ACV is above or below the average Target % ACV reference.  The reference we use in this analysis could be the average U.S. food banner.

In this example, there are a few Albertsons’ local banner stores that are of great interest to us. In Lucky, Pavilion’s and Randall’s, our target shopper accounts for almost 50% or more of the estimated ACV of these banners. That equates to every $10 that is spent at these banners, our target shopper is contributing about $5. For a new emerging product, it’s really important that we find its loyal consumers as efficiently and effectively as possible.  This method finds high propensity HHs without having to distribute or sell the product. We are applying a consistent approach across all retailers using HH actual purchasing (buying a product) and shopping (spending at a retailer) to inform the results.

This information allows us to identify where we can place the product — in retailers that help them build loyalty and the right assortment to important shoppers.  As a standalone measure, manufacturers and retailers use target % ACV to help identify where to have secondary placements, in-store events and initial roll-outs.

The next set of measures we are going to look at addresses at which retailers is there a reasonable opportunity to make the most money this year. Again, let’s look at the measures and then provide some explanation. In this example, I’ll go to the store-level.

Again, allow me to provide the definition of all the measures and then we can discuss.

Household Index: A measure of the store size based on the share of wallet a HH accounts for from that retailer and the number of households in the trade area. One group of HHs can spend $1,000 per year of their share of wallet at Costco and another group of HHs spends $4,000 per year. It will take four-times as many of the first group of HHs to equal one HH in the second group.  Sum up all the HHs shopping at the Costco’s and divide by a reference — in this case, the average club Store. In this example, the Costco located at 4502 East Oak St. in Phoenix, Arizona, is 34% larger in size of HHs than the average club store. This value is not product specific. As long as we use the same reference, it will be the same value.

Profile Alignment Index is the potency of the product’s sales per HH for the store to the average sales per HH in the reference banner. This measure indicates whether the average shopper in the store has a propensity to buy more or less of the product than the average shopper (in this instance, the average club shopper). This measure is product specific.  In this example, the average Costco shopper at 4502 East Oak St. in Phoenix, Arizona, has the propensity to buy 23% more product than the average club shopper.  This is very important for decisions.  Even if the HH Index is low, higher than average profile alignment index stores are great opportunities for new emerging products.

Product Potential Index is the comparison of what the product should sell in this banner relative to the average club store, given the same conditions for this product over the last 52-week time period. One can see that size of the HH index times the potency of the profile alignment index will equal the product potential. The Costco at 4502 East Oak St. in Phoenix, Arizona has size (134 Index) and potency (123 Index), therefore its product potential is 166.  We really need to get this product in that store.  However, there are two other Costco stores where the product potential is even higher, due to the size of the stores.

Product Potential Dollars is the dollar amount the product should sell in this banner given sales and sales conditions over the last 52 weeks at club. We use proxies for the new emerging product to provide a sense of the magnitude for a store’s sales expectation without using it as a predictive measure.

This bears repeating from the last interview. Is this measure predictive? Product potential is forward-looking, but it is not predictive.  We use past behavior to provide a consistent value across the retail locations and products IRI tracks. The information accounts for the last 52 weeks of pricing, price differential and support. What is important to understand about this product potential index and product potential dollar value is for sales, marketing, and operational purposes, not for investment purposes.  IRI can provide predictive modeling and new product simulation tools but that’s a different solution and requires different inputs.  Let’s leave that for a different conversation.

Manufacturers and retailers use this measure to understand where to place the product for best sell-through. Let’s put these measures together in what we call the activation grid and understand how it helps lead to different store prioritization strategies and tactics.

In the store activation grid, the target % ACV index is on the y-axis and the product potential index is on the x-axis. We recommend that you focus on banners and stores that reside in the upper right quadrant. It is important to do for existing products and even more so for new emerging products. Minimize what you spend on stores in the lower-left quadrant. Be smart about how you spend on distributing your product in the upper-left and lower-right quadrants. Build your brand and retailer relationships for the right reasons in the upper-right quadrant.

We all talk about risk management and focusing on the areas that make the most difference. Time and time again, I listen to companies discuss how they have to be in a particular retailer. Too often that retailer is good, but isn’t driving sufficient sales or that location turns out to be inappropriate for the product.  I’m getting pulled in at that point because now the risk of de-listment or the specter of poor performance necessitates an extraordinary effort.

The process that I go through is the very similar to what I have laid out here. There’s no reason to “roll the dice” on whether your retailer prioritization and their store roll-out is going to more or less successful. We can effectively and efficiently manage that risk from the beginning.

Let me end with an example. A client had a new product for a premium baked item. They approached a retailer who like the product but didn’t believe it “fit” their shopper and turned it down. The retailer was correct. It didn’t fit their “average” shopper; however, we found that 20% of their locations had a large concentration of the target shopper and higher levels of product potential.  The retailer recognized that these locations didn’t follow the average store sales. That product generated $6 million in 12 months at that retailer. This was one product at one retailer; it did not need to be in all of the stores.

Be strong where your biggest opportunities are and don’t expend your precious resources — money, time or effort — on the places where opportunity are not apparent at the moment.  There are enough places and revenue in places where the data is indicating to go than to take an undue risk.

How could analytics and insights help your companies’ brands?

MMI Brands is in a strategic alliance with IRI, a global leader in syndicated sales data and market research, to develop new and emerging brands introduction initiatives.

Robert Berg has been working in the CPG industry for more than 25 years. After earning an MBA from The Wharton School, Robert began his career at Coopers & Lybrand Consulting and PriceWaterhouseCoopers Consulting. Working for IBM Global Business Services, Robert worked on one of the largest CPG mergers in 2001. During his 13-year tenure with IRI, Robert has focused on rolling out new solutions for both CPG manufacturers and retailers and is currently working with mid-market clients. He is also charged with helping IRI clients receive the greatest value from their investment in IRI’s consumer and shopper solutions.

  1. What are some of the ways manufacturers and retailers should know about IRI’s new solutions?

Companies are looking to improve revenues and reduce costs on non-value added activities. To do this, companies typically compile detailed market information so they can focus resources on the high value opportunities and align products to where demand is and limit exposure to areas that represent higher than average risk without the appropriate return. I came to IRI because I saw the value of helping companies get these insights faster, at a lower cost and in a better format. I have been able to accomplish this across the CPG product categories and retailers.

IRI has sophisticated tools that provide insights on where to execute in a very simple way. The IRI ShopperSights™ solution gets to four basic questions very quickly and economically. In fact, the answers to the following questions can really focus the organization:

  •   Who are your most important households?

–  Are they ones that will spend the most on your product over a year? Are they the ones that will purchase the most when they buy? Or, are they the households that have purchased it at least once over time?

  •   Where do they live in higher concentration?
  •   At which retailers or stores do they shop at higher concentration (even if your products are not offered there currently)?
  •   At which retailers do you have a reasonable opportunity to make the most money this year?

Good management keeps the focus of the business on what’s really important. They want information systems that are data-driven and allow the organization to coalesce around one version of the truth: Where are we driving the most value? At IRI we’ve developed solutions that do just that.

  1. That sounds too good to be true, what’s the catch?

If there’s one catch to this, I think it’s that you have to be data-driven and believe in math. This can be threatening to some. With ShopperSights, IRI is using propensity modeling to take actual, demonstrated purchasing and then give each U.S. household a score for their propensity to buy a product (that IRI tracks – over 2 million current items) and shop a retailer (that are in the IRI retailer universe—close to 1 million retail locations in food, drug, dollar, club, mass, convenience and food service retail channels).

We’ve developed a proprietary modeling approach on trade areas for these locations that start with where each household would shop, given the retail options to which they can easily drive. We use Experian Mosaic Clusters as a building block for our shopper targets because it’s an affinity based clustering approach that reflects common identities, such as ethnicity, regionality, economic situation, etc. Mosaic identification is readily available for marketing/media contact tactics and enables our clients to communicate with their targets if they so choose. It is also linked to Simmons National Consumer Survey, which connects one’s product purchasing-based target to media, attitudes, values and lifestyle preferences.

The Mosaic 71 clusters provide flexibility to fine-tune targets by more than just purchasing behavior. We can add or remove based on prevalent demographic attributes or attitudes to Internet, outdoor activities, or health/wellness and family values. I characterize this as crafting a target to better serve our clients’ purposes.

This is a lot to take in and process. As you can see, there’s a lot of data running through an advanced analytical process on one of the most sophisticated IT platforms, so it can be a daunting task to full comprehend. I believe the most successful business people bring values, passion and clarity. Data-driven approaches allow a company to coalesce around what is happening in the marketplace and that helps to craft a story that brings clarity. When you use IRI’s solutions, you get data-driven solutions that you can incorporate into what makes your company unique and tell your story with the best possible insight into your consumers and the right retailers.

  1. What are the unique insights that someone using this solution would get and the value they would receive?

Clients get clarity on what’s important and explain this reasoning to their retailers and media partners. There are two powerful and proprietary measures IRI delivers from the ShopperSights that you can’t get anywhere else. These two measures are built from the household up. We encourage our clients to continue to use their top-down measures and then triangulate opportunities.  These two measures provide the insight on where to focus your sales effort.

First, we provide a dollar value and index for how much a “current” or “aspirational target” shops a particular retailer or store. To gain sales quickly, go to where your target consumer is already shopping in larger proportion or in larger absolute dollars. For instance, if you knew that a lake had twice as many fish as any other lake and your goal was to catch as much fish as possible that day, then you would ensure that location had adequate resources before allocating to the next location.

In addition, knowing how important a shopper is to a specific store is information that retailers want to know. They want to know that you are aligning to important shoppers for them. As a converted shopper for that retailer, there’s a better chance we can grow their basket by getting them to buy your product incrementally. This may appear to be a rhetorical question; however, we see companies over-spending to have their product distributed because of a personal or existing relationship. It’s not that the location is not where you need to be, the resource allocation has to be appropriate to the opportunity that location represents.

Second, we use existing buying behavior to calculate the potential buying behavior for your product or proxy for your product (if it’s new or has low volume) at the household level and then aggregate by retailer. Since we are calculating the share of wallet each household spends at each retailer, we are getting a better view of what each retailer should sell. By combining how much share of wallet each retailer receives from each household in that area with how much each household would spend on that product, we provide a reasonable value for what the product potential is for that store currently and then we roll up the stores for banner, retailer or area. As the product’s sales grow, the product potential will grow.

Is this predictive? It’s forward-looking, but it is not predictive. We use past behavior to provide a consistent value across the retail locations and products IRI tracks. The information accounts for the last 52 weeks of pricing, price differential and support. IRI can provide predictive modeling and new product simulation tools but that’s a different solution and requires different inputs.  That’s a completely different conversation. Better pricing, more focused support and better retail execution all can deliver better results.  The corollary is true too; poor pricing, limited support and inconsistent retail execution will challenge results.

What is important to understand about this product potential index and product potential dollar value is for sales, marketing, and operational purposes, not for investment purposes. This measure allows you to have a consistent view of where your best opportunity is across a wide range of products, retailers and geographies.  It allows you to focus your resources on the areas where the greatest probability for success is and manage your risk in areas where there may not be as much upside – for a reasonable investment and quickly delivered.

How could analytics and insights help your companies’ brands?

MMI Brands is in a strategic alliance with IRI, a global leader in syndicated sales data and market research, to develop new and emerging brands introduction initiatives.

Robert Berg has been working in the CPG industry for more than 25 years. After earning an MBA from The Wharton School, Robert began his career at Coopers & Lybrand Consulting and PriceWaterhouseCoopers Consulting. Working for IBM Global Business Services, Robert worked on one of the largest CPG mergers in 2001. During his 13-year tenure with IRI, Robert has focused on rolling out new solutions for both CPG manufacturers and retailers and is currently working with mid-market clients. He is also charged with helping IRI clients receive the greatest value from their investment in IRI’s consumer and shopper solutions.

  1. What are some of the ways private equity groups and investment banks should know about IRI’s new solutions?

Companies are looking to improve revenues and reduce costs on non-value added activities. To do this, companies typically compile detailed market information so they can focus resources on the high value opportunities and align products to where demand is and limit exposure to areas that represent higher than average risk without the appropriate return. I came to IRI because I saw the value of helping companies get these insights faster, at a lower cost and in a better format. I have been able to accomplish this across the CPG product categories and retailers.

IRI has sophisticated tools that provide insights on where to execute in a very simple way. The IRI ShopperSights™ solution gets to four basic questions very quickly and economically. In fact, the answers to the following questions can really focus the organization:

  •   Who are your most important households?

–  Are they ones that will spend the most on your product over a year? Are they the ones that will purchase the most when they buy? Or, are they the households that have purchased it at least once over time?

  •   Where do they live in higher concentration?
  •   At which retailers or stores do they shop at higher concentration (even if your products are not offered there currently)?
  •   At which retailers do you have a reasonable opportunity to make the most money this year?

Good management keeps the focus of the business on what’s really important. They want information systems that are data-driven and allow the organization to coalesce around one version of the truth: Where are we driving the most value? At IRI we’ve developed solutions that do just that.

  1. That sounds too good to be true, what’s the catch?

If there’s one catch to this, I think it’s that you have to be data-driven and believe in math. This can be threatening to some. With ShopperSights, IRI is using propensity modeling to take actual, demonstrated purchasing and then give each U.S. household a score for their propensity to buy a product (that IRI tracks – over 2 million current items) and shop a retailer (that are in the IRI retailer universe—close to 1 million retail locations in food, drug, dollar, club, mass, convenience and food service retail channels).

We’ve developed a proprietary modeling approach on trade areas for these locations that start with where each household would shop, given the retail options to which they can easily drive. We use Experian Mosaic Clusters as a building block for our shopper targets because it’s an affinity based clustering approach that reflects common identities, such as ethnicity, regionality, economic situation, etc. Mosaic identification is readily available for marketing/media contact tactics and enables our clients to communicate with their targets if they so choose. It is also linked to Simmons National Consumer Survey, which connects one’s product purchasing-based target to media, attitudes, values and lifestyle preferences.

The Mosaic 71 clusters provide flexibility to fine-tune targets by more than just purchasing behavior. We can add or remove based on prevalent demographic attributes or attitudes to Internet, outdoor activities, or health/wellness and family values. I characterize this as crafting a target to better serve our clients’ purposes.

This is a lot to take in and process. As you can see, there’s a lot of data running through an advanced analytical process on one of the most sophisticated IT platforms, so it can be a daunting task to full comprehend. I believe the most successful business people bring values, passion and clarity. Data-driven approaches allow a company to coalesce around what is happening in the marketplace and that helps to craft a story that brings clarity. When you use IRI’s solutions, you get data-driven solutions that you can incorporate into what makes your company unique and tell your story with the best possible insight into your consumers and the right retailers.

  1. What are the unique insights that someone using this solution would get and the value they would receive?

Clients get clarity on what’s important and explain this reasoning to their retailers and media partners. There are two powerful and proprietary measures IRI delivers from the ShopperSights that you can’t get anywhere else. These two measures are built from the household up. We encourage our clients to continue to use their top-down measures and then triangulate opportunities.  These two measures provide the insight on where to focus your sales effort.

First, we provide a dollar value and index for how much a “current” or “aspirational target” shops a particular retailer or store. To gain sales quickly, go to where your target consumer is already shopping in larger proportion or in larger absolute dollars. For instance, if you knew that a lake had twice as many fish as any other lake and your goal was to catch as much fish as possible that day, then you would ensure that location had adequate resources before allocating to the next location.

In addition, knowing how important a shopper is to a specific store is information that retailers want to know. They want to know that you are aligning to important shoppers for them. As a converted shopper for that retailer, there’s a better chance we can grow their basket by getting them to buy your product incrementally. This may appear to be a rhetorical question; however, we see companies over-spending to have their product distributed because of a personal or existing relationship. It’s not that the location is not where you need to be, the resource allocation has to be appropriate to the opportunity that location represents.

Second, we use existing buying behavior to calculate the potential buying behavior for your product or proxy for your product (if it’s new or has low volume) at the household level and then aggregate by retailer. Since we are calculating the share of wallet each household spends at each retailer, we are getting a better view of what each retailer should sell. By combining how much share of wallet each retailer receives from each household in that area with how much each household would spend on that product, we provide a reasonable value for what the product potential is for that store currently and then we roll up the stores for banner, retailer or area. As the product’s sales grow, the product potential will grow.

Is this predictive? It’s forward-looking, but it is not predictive. We use past behavior to provide a consistent value across the retail locations and products IRI tracks. The information accounts for the last 52 weeks of pricing, price differential and support. IRI can provide predictive modeling and new product simulation tools but that’s a different solution and requires different inputs.  That’s a completely different conversation. Better pricing, more focused support and better retail execution all can deliver better results.  The corollary is true too; poor pricing, limited support and inconsistent retail execution will challenge results.

What is important to understand about this product potential index and product potential dollar value is for sales, marketing, and operational purposes, not for investment purposes. This measure allows you to have a consistent view of where your best opportunity is across a wide range of products, retailers and geographies.  It allows you to focus your resources on the areas where the greatest probability for success is and manage your risk in areas where there may not be as much upside – for a reasonable investment and quickly delivered.

Blue Bell Ice Cream

In April 2015, Blue Bell brand voluntarily recalled all of its products on the market made at all of its facilities including ice cream, frozen yogurt, sherbet and frozen snacks because they had the potential to be contaminated with Listeria monocytogenes.  This presentation analyzes the recovery of the Blue Bell brand before, during and after the 2015 recall.

MMI Insights – Blue Bell

The State of Foodservice 2017

The National Restaurant Association’s 2017 State of the Industry report is the most comprehensive outlook and overview of the quickly evolving U.S. restaurant industry.  This comprehensive report, which projects industry sales of $799 billion in 2017, serves restaurant operators, industry analysts and suppliers the deep data, insights and most up-to-date industry trends available to increase sales, identify opportunities, develop growth strategies and more.

State-of-Foodservice-2017