Shopper Insight

In Retailwire,  IBM/DemandTec sponsors an interesting paper: Shopper Insights: Actionable or Academic?  An overview of a survey on the topic.   Our innovation centers were established in part to fine-tune an understanding of the shopper from a number of different resources.  From our own experimentation, from the knowledge of our consumer researchers, and from leading edge research done by internal and external vendors. DemandTec was an early visitor,  where we talked about the effectiveness of planning promotion and assortment, using analytic methods.    The paper suggests, as we saw early on:

" ... Shopper insights are here to stay, according to RetailWire’s recently conducted study of industry  professionals and practitioners, and are quickly becoming a “must-have” feature of decision-making relative to category management, merchandising, marketing and in-store activities.In particular, shopper insights derived from specific retail accounts are seen as beneficial for fostering strong collaboration between supplier and merchant. Said one respondent: “It is the new currency to drive retailer/manufacturer collaboration to work jointly to improve the business/category.” ... " 

So we clearly saw the early need for learning that was more than academic.  And produced results that could be applied early to our own mix of products and could take our understanding of the consumer, for new products and new initiatives, and combine that with operational retail knowledge.

This paper studies insights from a survey in late 2010:  " ... The study sampled information and opinion from 593 executives and managers.  Supermarket/grocery retail and manufacturer companies were most strongly represented  in the sampling, and nearly half of respondents are in upper management positions. ..." 

Worth reading for its results.  As an excerpt I always like to look at future actions, since my role was always of a futurist and technologist, and this was interesting:

" ... both retailers and suppliers expect that manufacturers will partner relative to shopper insights with more than the number one retailer in a particular market. Indeed, only 2.5 percent of the  total number of survey respondents say that a supplier should only partner with the market leader and  go no further. From the supplier viewpoint, 20 percent answer that going beyond the market leader  should be done to enhance more retail relationships, while 69 percent say that working with more than one retailer in a particular market should certainly be done for relationships, but also for gaining  additional knowledge for HQ planning.... " 

I am incorporating some of this data in a study I am doing.  Please send me any further insights you have.

IBM/DemandTec Assortment Optimization

Early in my career I was given the task of how to optimize assortments under the constraints of the market shelf. On the surface the problem looks easy.  You have a set of possible products you want to place on shelf.  You have the value of each of the products to the manufacturer or retailer expressed by profit or historical demand, you have the constraints of space on the shelf.  You may also have design constraints that tell you what products 'should' be placed next to others based on consumer behavior understanding.   Plus a lot of additional and sometimes subtle constraints.  All this can be expressed mathematically, using well known methods that have been known for a long time.  But it turns out the resulting expression is complex and difficult to solve.   We explored how to do this and found it daunting.  So I was very impressed when I first saw an example of how DemandTec did assortment optimization for retailers.  Their method cuts to the chase to increase profitability for retailers based on historical demand while also including the shopper in the model.  They write:

" ... No more guesswork.  The best assortment for each location. The best assortment is the one shoppers expect to see on your shelves, but also the one that delivers the best profits.  So why make guesses? IBM DemandTec Assortment Optimization offers a collaborative approach for defining localized merchandise assortments through a complete understanding of what drives buying decisions – incorporating shopper demand, space, productivity, and profitability. .... Now you can offer items that meet unique demands or targeted shopper segments.  You'll know exactly which items you can replace or substitute for other items in your portfolio.  Most importantly, you'll understand the implications of various assortments on each customer segment. With one common view of the shopper, their decision trees, and the marginal additional value of each SKU to the equation, manufacturers and retailers can work together more effectively to delight shoppers and build customer loyalty. ... " 

DemandTec/IBM Shopper Insights

Our own enterprise was devoted to the art and science of being shopper centric.   Decades of research allowed us to leverage that capability against the needs of the consumer.   Centricity was the key to making the system work effectively.  I discovered this piece in the Demandtec/IBM site which coves some of the same concepts.  And mirrors some of our own thinking.  They write:   " ... Of course each shopper is unique – and supporting shopper centricity gives you and your trading partners a competitive edge. But how do you actually harness key insights on the value of the shopper?  How do you offer the best rewards that truly excite consumers and drive long-term growth? ... " 

And how do you harness the insights?  This is once again a combination of running the numbers, doing the analytics, but also driving the insights with new design ideas to make them work.   In part this is about dividing up the problem properly:

... With IBM DemandTec Shopper Insights, you can take action on critical insights across the entire business planning lifecycle.  Set broad corporate strategies.  Determine key target segments. Collaborate with partners and flawlessly execute marketing and merchandising plans... 

The benefits are outlined:

"  ... Stand out from the competition by adopting more shopper-centric strategies
Understand consumer demand by shopper segment
Deliver actionable shopper insights at the point of decision ... " 

Utilizing new ideas at the point of decision was particularly important.  The First-moment-of-Truth was preached as the means to success.  As the first moment of truth crept  to different contexts and media, such as mobile and online,  the adjustments were made to capture these places with new designs and measure the results with the right data.

Note this is by its nature a big 'big data problem' (Volume, volatile, complex and real-time).  The dive using analytics needs to be deep, with the latest technologies.    We continue to win with these methods.

IBM DemandTec for Marketers

From IBM DemandTec, a good view of the need to construct valid shopper segmentation.  Why?  So we can use targeting to make sure the right consumer gets the most influential message.  The link goes to an infographic and further  information on this concept.

New techniques are now available to make it easier to do.  Relationship and social marketing allow the integration of new and precise marketing methods.  Linking this further to marketing mix methods, minimizes   cost to achieve a particular return.  To take this further.   And more at the link:

1. Use advanced science and shopper segmentation to better understand shifts in consumer demand and connect with individuals and segments rather than broad markets. Merchants can now surface those insights right at the point of decision of pricing, promotion and assortment activities. By recognizing that each shopper is unique and responds differently, revolutionary merchandisers can tailor strategies to focus on their most valuable shopper segments – providing differentiation at the shelf and a real path to category growth.

2. Stay relevant with intelligent targeting
Invest in capabilities designed to manage the entire promotion lifecycle – from analytics to deployment. Target promotions not with a broad brush, but by shopper segment through localized and automated ad versioning across virtually all customer touchpoints. An integrated planning environment can keep your marketing counterparts on the same page as your team throughout the planning cycle, translating into greater visibility, improved quality, and ultimately more time to focus on strategic issues.

3. Capture value, measure results
Increase marketing ROI by aligning assortment, price, promotion and marketing decisions in a unified planning environment. A common platform also allows you to work more effectively with your merchandising team counterparts – helping teams to plan for category growth, new shopper attraction and behavioral impact on key shopper segments while allowing you to tailor your marketing investment to achieve financial goals..... "

IBM/DemandTec, New Partner Services

This is dated, but the application is interesting.  Just brought to my attention by a colleague.  We had looked at how competitive information could be integrated to analytic decision making.  In the past this was done on a 'what if' basis.  Using scenario planning methods.  Hand assembled and integrated data  with quantitative analyses.  Now the speed, breadth and volatility of the data required makes this difficult to do accurately.    The data involved is big and volatile.   There is also a requirement to infer intermediate conclusions to support the analytics.

" ... a collaborative optimization network for retailers and consumer products companies, have announced the availability of new services on the DemandTec network powered by new partners RivalWatch and FoodLink Online LLC.

Partner-enabled services are activated and delivered on the DemandTec network through the DemandTec Network Partner Program, providing a seamless experience for the community of 16,000 active network members. DemandTec customers will benefit from partner services that offer value-added content and functionality specifically designed to enrich and extend DemandTec capabilities. Partner services on the network leverage the strengths of a qualified partner ecosystem that closely aligns with the retail and consumer products industries, giving customers more flexibility and information to make business decisions.

"We've enjoyed a fruitful relationship with RivalWatch for more than two years and we believe the inclusion of RivalWatch's services on the DemandTec network will deliver significant value to the marketplace," said John Kittle, Retail Innovation and Analytics Manager at Ace Hardware. "There is a clear gap between competitive data and an analytical decision platform to activate competitive insights, and I'm excited to see how the new RivalWatch on DemandTec service fills the void." ... " 

Target Experience with IBM DemandTec

I was pointed to a video interview with Shelly Hyytinen,VP of Merchandising Process and Systems Development at Target Stores.   An excellent view of how Target was introduced to IBM DemandTec's use of optimization science to address price and promotional planning optimization.

In particular I liked this interview because it also dealt with how deep analytics could be sold to the internal users of the 'art' of promotion. This is another example of the combination of design and analytics mentioned a number of times in this blog recently.   You still have the experience of old style merchants, but now how they can be empowered by new technology analytics.

The video also includes some specifics of how Target is using analytics to better understand their 'guests'.   And having been involved with them from the suppliers perspective,  the increasing importance of the ability of the retailer and the supplier working from the same set of historical and forward looking data.

Finally, a look at how strongly Target believes in the future of retail analytics, and the need to predict the expectation of mapping the needs for both online vs in-store channel consumer expectations.

Excellent interview looking at the risks of new technology, their mitigation and the forward looking needs of both retailers and suppliers.

Target outlines their key benefits derived:

Combined user-friendly software with scientific algorithms that generate optimized decisions with predictive analytics

Helped Target merchants reap the rewards of a science-based approach to making core merchandising decisions about range and price
Improved sales units, dollars, and gross margin; enhancing customer price perception

#revdecisions

Strategic Marketing Mix Decisions

I have been recently been taking a look at the broad concept of marketing mix decisions.  The problem is old:  how do we decide how much promotional dollars to allocate to what marketing medium?  How much are we wasting?   And how do we time the allocation to make sure it optimizes the results achieved?   It links to the general problem of forecasting demand.   Forecasting depends upon both specific company decisions and external uncontrollable contexts we need to consider.  When I taught forecasting I always included the   phrase 'The forecast will be wrong, but how will it be wrong is the more important question'.  

In recent years too the number of possibilities for forcasting methods has expanded.   Online and social methods, still in their relative infancy, also need to be allocated funds to make them work.   How do you react to rapid changes by competitors?  And the question of how much and when immediately emerges.

I have been taking a look at IBM DemandTec's approach recently to understand how it it integrates with other methods on the market.   My enterprise tested their approaches early on. Their holistic approach based on optimization methods bears a close look. They write:

" ... Holistic marketing mix decisions.  One continuous, actionable plan..... Simply using average marketing investment returns doesn't tell you much about what's driving volume, share, or profit.  If your assumptions are stale, you can't truly optimize your marketing mix in a rapidly changing marketplace. Now you can use the most dynamic predictive tools available to optimize marketing investment decisions throughout the year.  It's all delivered through one comprehensive system.

IBM DemandTec Strategic Marketing Planning transforms traditional marketing mix insights into one continuous analytic system that spans all of today's consumer touchpoints – media, trade, social, and more.  Empower CMOs with sophisticated tools for allocating portfolios.  Give brand managers precise up-to-date data to optimize decisions. .... 

Quickly adapt to marketplace shifts

Optimize marketing spend

Efficiently allocate marketing funds

Fully leverage your existing marketing mix analysis investment   .... " 

Achieving Smarter Commerce: IBM and DemandTec

I have been following DemandTec (Now part of IBM) since they presented at our innovation centers soon after they were formed.  I was impressed by the deep analytics they were using.  Since then I have connected a number of times,  visited twice, and in the last few months have posted a number of items here about their progress.  Then last year it was announced that IBM had announced its intent to acquire DemandTec for their smarter commerce initiative.  An acquisition that makes considerable sense. I had also attended some of the IBM road show on analytics applications, and saw how they were seeking to tie together a number of acquisitions that could interlinked and then be leveraged to 'smart' capabilities in general.  What I saw looked good.  Here is another example of their views on marketing.  And how they link to IBM's smarter commerce initiative.

Revolutionizing Trade Strategy: Science and Shopper

I recently happened on an article by DemandTec on trade strategy.   Five ways to revolutionize your trade strategy.  A well put set of suggestions that emphasize the analytical aspects of addressing strategy.  Notable in particular was the idea that companies need to increasingly 'use science' to deliver more precise solutions.   In this discussion I emphasize two areas, this aspect of science, and the goal of really understanding the shopper.

We live in an era where there is an increasing amount of behavioral data about how shoppers interact with shelf, promotion, and ultimately buy.   We even have increasing amounts of data about when the shopper is in new locations, like when they are on the move with their own devices.  We can even infer when the shopper is just thinking about purchases,  while looking for reviews, or scanning for alternative prices.  I did a study of of this kind of consumer behavior during the early days of smart phones.  In the lab and then in real stores.   Did this new behavior empower the shopper or embarrass them?  This spectrum has been steadily evolving.

This sets the stage for both strategy and tactics for retail decisions.  And another item that is mentioned:  Getting shopper centric.   The shopper centers themselves upon much more than just the latest promotions.  They are part of a household, and keenly sensitive to their needs.  They see ads on TV,  on the Internet, and increasingly on their mobile devices. Flyers come to their home, often tailored to the purchases recorded on their loyalty card.

As they walk through a store, they are attracted by in store fixtures and  new product announcements.   Digital screens on the shelf and above them on the wall and ceilings attract their attention.  Increasing numbers of choices are displayed.  Announcements of new products are also interleaved between this exposure in the aisle. Inserting new brand decisions among a flurry of old thoughts.  Can I use that in a recipe?  Will this fit my budget?  Will my household like this new thing?  Three hundred and sixty degrees of decision making in an increasingly tailored retail environment.  The complexity and depth of this new decision making is considerable.

As the article suggests, the 'nuances' of these interactions can be recorded in new ways to allow the tailoring these preferences locally, and leading to better strategic decisions.   New data and larger databases will allow the continued tailoring of the experience.   Newly derived Big Data methods will make this easier to do.  It is a challenge I will be following.

Segmentation plus Merchandising

Merchandising has been around for a long time.  We did lots of experimentation trying to understand the specific behavior of consumers in laboratory, virtual and actual stores.  In each case with carefully interviewed real shoppers.  We also sought to understand how these 'old' behaviors linked to new behaviors like those online, and especially in mobile settings.   It all comes down to the specific behavior of consumers in this rapidly changing domains.     How does the behavior of people online and in brick and mortar vary?   General segmentation of these behaviors has always existed, but how is it known quantitatively and accurately?   Leading to specific decisions that can lead to lower costs and increased profits.   This is a relatively new challenge for analytics.

In a recent RetailWire, this is expanded,  note the mention of three decades work, which I participated in from both the experimental dimension and dealing with the data itself:

" ... Say your final farewell to the mass market. It's taken at least three decades of work and experimentation but, thanks to technology, truly customer-focused, targeted merchandising and marketing is now finally possible.  Data analytics now gives retailers the ability to define their customer segments based on shopper needs, behaviors and traits, and specify marketing approaches that meet the demands of each segment ....  As discussed in a recent Shopper-Centric Retailing eBook produced by DemandTec, an IBM Company, combining merchandising optimization technology with shopper segmentation now gives retailers the power to identify and incorporate a host of segment behavioral differences into their merchandising and marketing decisions..... " 

The power is suggested is considerable, especially when linked to new engagement capabilities: in-store, on mobile, and producing accurately tailored merchandising.     It also connects well to the levels of investment made in each of these contexts.  Marketing mix is a challenging process.  Improving and even optimizing the results are now made possible by a new realm of data that now makes possible new accuracy in merchandising.

Read the short article linked to above and the full white paper attached for more detail.   I am optimistic that we will continue to see improvements in this area.    More data and improved analytics will lead the way.  Smarter commerce will result.

So What is Best Price?

What is the right price?    It is always a tough question in retail.  Prices map to profits, and also strongly influence how consumers regard the retailer, both about a particular product and about the retailer in general.    Prices are increasingly transparent.    I was involved with a study recently which looked at how shoppers are increasingly using smartphone scans to compare prices on all sorts of products in-store.   The scans can easily be stored so they can use their laptop at home later to investigate alternatives.   Now people are no longer afraid to do a scan.    The world has changed.  When I asked them what they were doing when scanning in the store, they emphatically said things like:  'Making sure I am getting the right deal".

The scan also provides you with new kinds of information to structure how you intract with product choices.  The challenge is on. How do you assure you do have the right price to not scare off the shopper and still make a profit?  How does this relate to your long-term relationship with the shopper?   With promotional choices?   The increasing trasparency of prices to the consumer makes this crucial.

We talked to DemandTec as early as 2002 to better understand their methods.  I was impressed by their approach in category data and price management.    A unique quantitiative model that we had thought of,  but were unable to solve at the time.

They have come out with a paper regarding a customer success story for a direct delivery e-grocery, FreshDirect.   Also a concept we examined in some detail to understand one future view of grocery.  It is an ideal example of how to leverage cost, price and behavioral data that leads to new kinds of convenience for the online consumer that still needs physical goods.   By its interactive nature it can leverage new kinds of acquired data.

Check out their white paper for more details about how FreshDirect leverages their unique data to better serve their customers with the right price and product offerings, and build stronger loyalty to the convenience of FreshDirect.

FreshDirect is a pure play e-commerce retailer. As such, the data available to them provides a unique opportunity for competitive differentiation. "We know precisely every purchase for every customer, and a lot of surrounding behavioral data. We also have absolute compliance with all our pricing changes with absolutely no effort," ... 

 FreshDirect had a unique opportunity to leverage its data and allow it to compete more effectively. Thus, FreshDirect decided it needed a price optimization solution and DemandTec's Everyday Price Optimization software service on the DemandTec network fit the bill.

Locately Shopper Intercept

Locately on DemandTec.   I was recently pointed to this path-to-purchase approach that I had not heard of before.   An example of an instrumented component, or sensor, that can be attached to shopper behavior.   Leading to smarter commerce.  This has been an interest of mine since the innovation center formation.  The connection to DemandTec's analytical techniques creates a whole new sphere of business analytics.

"Locately provides actionable reporting on actual path-to-purchase and shopper word-of-mouth, directly accessible from within the DemandTec network. Shoppers are invited to join Locately's 100% opt-in smartphone shopper panel. Locately's patent-pending platform then automatically detects which stores shoppers visit based on data from their mobile phones... In addition, Locately's platform sends targeted "in the moment" mobile surveys to shoppers when they are at the store, to understand what they think and why they make the choices they do....   Locately on DemandTec provides customers with insights to essential shopper behavior including:
Competitor analytics
Which rivals do my shoppers cross-shop at and why?
What is my market share of foot traffic in the channel?
When do shoppers drive past my store to go to a competitor, and vice-versa? Why does this happen? ..." 

Free Shopper Centric e-Book

From DemandTec.  This was precisely the approach we emphasized for many years within the enterprise.  It is all about how the shopper behaves in their increasingly changing locations.  It is about the point of decision.  Personalized in the aisle, on a smartphone, on a tablet.   If you don't know the shopper, you cant influence the decision.    I like their header 'The Mythological Average Shopper'.

" .. With the explosion of mass retailing, the customer became an abstraction and all were treated the same. The turn of the century saw the advent of new, powerful technology designed to enable demand modeling, forecasting and optimization that support superior planning and performance.   Learn how next generation technology is ready to help renew our intimacy with the shopper, target our plans, and deliver competitive advantage  .... "

Tailoring Analytical Insights at the Point of Decision

DemandTec is now an IBM Company, but I am continuing to make my way through their solution briefs for retail.  This week I took a look at one that I had not reviewed before, their brief on shopper insights.  Shopper insights were a particularly important piece of our laboratory work.  Constructing specific experiments to understand the actual behavior of a shopper in a particular context.  How might they be influenced by store design,  packaging and technology meant to influence their consideration and engagement with the retail environment?

As the article suggests, each shopper is unique.  '.. in terms of their value to the retailer and their response to merchandising and marketing activities ... '.      My own background used principles of modeling and statistics, applied to what is now called business analytics ... to create models of the consumer and their environment, based on the data gathered from these experiments.

They show a number of dashboards as part of their Shopper Insight Center that are designed to answer specific questions about  key retail processes.  This is exactly what we were thinking of producing in the lab environment.    As in any business analytics solution the problem is to connect the data gathering step with the specific process or workflow of the system you are interested in.  A set of simple dashboards is a good place to start. 

A set of dashboards, as the report suggests, can then be tailored to specific questions you are interested in exploring about the adjustment of shopper engagment in the retail environment.  I had seen similar things done to great advantage in Casino environment.  Once the simple dashboard environments are constructed, the data can then be tailored to address more in-depth analytical interaction with the data. Leading to precisely tailored analytical insights for any context.

Read the rest of the brief at the link above.

Key Developments in Integrated Retailer Marketing and Merchandising

In the IBM smarter commerce blog.  A post that relates directly to the DemandTec acquisition.  It extends beyond to the 'social' integration and communications  all the way back to the manufacturer of retail products sold and their suppliers.  There is lots of potential here.   Further, how do you get the right information from the retail selling space to improve the operation of commerce?  I have been talking to a  company called Storeflix that has developed methods to make that happen through the smartphone.  It is what the smart commerce initiative calls the 'instrumented' component.  Much happening in this area today.

IBM Announces Completion of DemandTec Acquisition

Announced today.  The integration of the DT abilities into IBM's Smarter Commerce effort makes much sense.  Looking forward to see the details of how it will all integrate together.   I have followed DT here since their first presentation to our innovation center in 1999:

" ... IBM Smarter Commerce on Cloud gives companies broader insights about customer merchandising and pricing preferences to better market, sell and deliver their products and services," said Craig Hayman, General Manager of Industry Solutions at IBM. "With IBM and DemandTec, marketing and sales executives in retail, CPG and other industries will be able to deliver the best prices and product mix based on consumer buying trends."

DemandTec delivers cloud-based analytics software to help organizations improve their price, promotion, and product mix within the broad context of enterprise commerce: retail, business-to-consumer, and consumer goods. As a result, companies can spot trends and shopper insights to make better price, promotion, and assortment decisions that increase revenue and profitability. By gaining a quick analysis of consumer trends, for example, a category manager at a consumer products company can collaborate with the retailer to understand price elasticity and set a more competitive price point.... "

Gartner View of IBM DemandTec Acquisition

A short post by Gartner on the proposed acquisition.. Some of the usual watch-outs with any acquisition. Certainly it is a means of bringing very specific retail and manufacturer analytics to cloud based big data. And at the same time integrating social based solutions to help multiple players in this space interact effectively. From what I have seen since first being exposed to Demandtec methods at our Innovation Centers, this could be a magical way to improve business analytics.

Predictive Trade Planning in the Cloud

Press Release:

Unilever Selects DemandTec for Predictive Trade Planning in the Cloud
Global consumer goods leader drives more effective retail trade plans with predictive analytics

SAN MATEO, Calif. –December 7, 2011 - DemandTec, Inc. (NASDAQ: DMAN), the collaborative analytics cloud for retailers and consumer products companies, today announced that Unilever has selected Customer Trade Planning , a predictive trade analytics app on the DemandTec network.

By leveraging DemandTec, Unilever is empowering business users to create unified pricing and promotion plans that more effectively invest trade promotion funds. The predictive app will allow Unilever to better understand consumer demand to achieve brand objectives and support a more strategic level of collaboration with retail trading partners .... "

....

Numerical Algorithms and DemandTec

I have been talking to several companies about advanced analytical algorithms used for making choices about engagement practices for the enterprise.  A few new discoveries made:   " ... In today's highly competitive retail market retailers need the most advanced and up to date software capabilities to achieve advantage over competitors and maximize profits. DemandTec provides the retail and consumer products industries with Consumer-Centric Merchandising software, which enables the planning, optimization and execution of merchandising and marketing programs based on a holistic understanding of consumer demand. No other company has as broad a merchandising planning and optimization software suite as DemandTec, nor does any other vendor have the large number of successful deployments with blue chip companies around the world ...  

IBM to Acquire DemandTec: Delivers Analytics via the Cloud

I see in a press release that IBM has agreed to acquire DemandTec.    Our enterprise retail innovation center was an early evaluator of DemandTec, which brought advanced analytics to key retail and manufacturing  processes.  I was impressed that they had delivered approaches that we had long examined and leveraged to improve operational systems.  Aiming to deliver smarter commerce through analytics.

 Later, they were an innovator using social network interaction to help manufacturers and retailers to collaborate using business analytics.   This new acquisition looks to the Cloud to make those capabilities even easier to connect to data, provide analytics and share results.   This should add nicely to IBM's already impressive vertical analytics capabilities.  To see where this plugs in, see IBM's Smarter Commerce  initiative.

" ... The acquisition of DemandTec will extend IBM's Smarter Commerce initiative by adding cloud-based price, promotion and other merchandising and marketing analytics to help companies better define the best price points and product mix based on customer buying trends.

Organizations are struggling to meet the demands of rapidly shifting customer buying patterns in the era of mobile and social networks. This new digital marketplace requires companies to be highly responsive to consumer demands on the fly. Whether it's setting and executing the right pricing strategy or the ability to automatically adjust pricing based on online and offline data, being able to rapidly shift to market changes has become a key competitive advantage for global businesses ...  "