#CPG #CategoryManagers Take Note:  Smile, You’re on Consumer Camera

We’ve noted recently how beacon technology can track a consumer’s movement throughout the store and broadcast product specific marketing to the consumer using their smart phone.

Additionally, there is new technology that can use the existing security cameras and floor tiles to both watch movement and track traffic location throughout the store.

Of course this depends on the retailer investing in this technology, over which you as a CPG category manager or sales manager have no control.

But something you do control, or at least influence, is how, or if, you can analyze the resulting data once it becomes available.  Older DSR technologies, using database or data warehouse methods, are rigid and hard to change.  Adding new data streams takes months or years to incorporate – if attempted faster can break the data model making is difficult to load or extract data.  Difficult means time consuming.  Not what you need when your buyer’s meeting is 9am Monday and you are waiting on data loading (called ETL) and extraction (reporting) at 10pm Sunday night.

Big data is different – not just the buzz around it – but truly different from a technological point of view.

Big data allows you to add new, even unstructured data (think your latest spreadsheet creation), for analytics insights in hours or days.  So when this new consumer tracking data is made available to you analyzing and acting on it means you can take steps toward better promotions and product launches.

Big data technology is demonstrably faster in loading (literally minutes versus hours) and extraction and reporting.

Which would you rather do on Sunday night – sit at the office until midnight just waiting on your first peak at last week’s data – or home with your family watching Sunday Night Football?

Vortisieze is the first big data analytics package designed exclusively for the CPG community.

Contact us today and makes us prove just how fast Vortisieze can put you ahead of your competition.



Source:  Smile, You’re on Consumer Camera






ZuumSocial Releases Facebook Leaderboard – Most Engaged #CPG Brands on FB

Last month Zuum announced it will begin monthly ranking of the 25 most engaging brands on Facebook.  The rankings are limited to the top brands operating in the U.S.  This is how they summarized their criteria for selection:

The goal of this is to capture the Facebook content and community traits of the top brands operating in the US. So we’ve put several constraints on which brands are selected. Brands must be operating in the US, we’ll use the US page unless there’s only a global page, brands must be consumer products vs B2B, and we’re excluding technology and entertainment brands, as our goal is to better understand how typical consumer products work on social media, and both of those categories tend to skew towards extremely high engagement due to the product type.

For July and August Monster Energy Drinks captured the top.  This month Zuum has released the rankings for a specific category CPG Dips and Dressings.  Here is the lead-in to their rankings:

CPG is a very broad business category, with sub-categories like soft drinks having brands with some of the larger social media fan counts anywhere. In our July ranking of the 25 most engaging brands on Facebook, the three top brands are CPG.

Of course, the CPG umbrella includes many smaller brands, with more niche or regional appeal. One subcategory in particular is dips and dressings. Below is the Facebook Leaderboard for some of the top dips and spreads brands in the US for the month of July.

You can see that the fan counts, while not what you’ll see from Pepsi or Coke, are still substantial. Posting volume is a little light in this category, with even the top brand, Sabra, only posting about 1 time per day.

Once the novelty of these new rankings are gone what value does this have to a CPG category manager or sales analyst?  “Well – Nancy . . .” – if your analytics cannot lay this new, unstructured data alongside your retailer supplied POS and inventory data – there is no value outside of water cooler talk.

This is one of the major limitations of rigid, outdated, DSRs built using data warehouse technology.  Rigid in the sense that to add new data feeds takes months – sometimes years.  The loading of the data – including current feeds – is long and cumbersome.  From a technological point-of-view these simply will break under the weight of increasing amount and type of data.

If you want to use these new – and exciting – data points (social media, weather, and et. al.) to draw insights and correlations to sales – then the only technology that can pull this off – today – is Big Data.

That’s what the buzz is about.  Will your brand be buzzing going forward?

We are Vortisieze.

Contact us today for a complimentary consultation on your BI strategy.



Facebook July Leaderboard for CPG Dips and Dressings


Ranking 25 of the most engaging brands on Facebook


July Ranking of 25 Most Engaging Brands on Facebook



#Business Intelligence



NYC Shoppers (Still) Want Walmart

This very interesting article on yesterday reminds those of us who live and work in the shadow of the Walmart Home Office that there are areas where there is no Walmart store.

New York City is one such area – no Walmart exists within the five boroughs.  The mayor and most of the city council oppose Walmart entering NYC.

As the article points out – “25 percent of respondents go to the suburbs to shop Walmart stores. And it is obvious that many New Yorkers go to the burbs to shop other big box stores, discounters and outlet malls.”

The arguments against Walmart remain the same – and each one is Luddite in nature.

  • Walmart pays low wages. There is no denying that Walmart pay and benefits are modest by comparison, especially at the part-time and entry levels.  However, for people who just want jobs Walmart is the perfect place to start and learn retail.  And, Walmart hires from the communities around its stores.  Since the retailer appeals to middle to low income shoppers this means that those who need opportunity the most can find it – with the chance to move up the ladder in position and pay.  Additionally, those opposed to Walmart based on pay fail to look at the comparison of revenue per associate with other “high paying” companies – Walmart is at the low end of that scale.  And the margin of profit is much lower for Walmart, compared to other Fortune 500 companies, so there is a smaller pie to slice.  However, lower margins means lower prices – great for the consumers.
  • Walmart is anti-union. Walmart has worked actively against unionization of its workforce throughout its history.  Advocates of unions fail to demonstrate the benefit to their workforce.  By artificially raising the cost of labor unions in private industry have reduced available jobs so fewer people are working.  When the best hand-out is a hand-up through job opportunities how is limiting the number of jobs available helping the unemployed find skill training through work?
  • Walmart is hurting small, local businesses. On April 1, 1975 Walmart store #85 opened in my hometown.  Before then, only small, family-owned stores were available for items like hardware and clothing.  My mother drove my sister and I over 30 miles to the state capitol to shop at the large retail chains (primarily JCPenny for school clothes since her first job was as a clerk at JCP).  The local department store simply charged prices that were too high for my budget-minded parents.  Yes – after Walmart opened those businesses lost revenue and, over time, most eventually went out business.  What the critics fail to acknowledge is that Walmart has always offered lower prices for the budget minded.  As to the jobs lost through the shutdown of small, local business – Walmart more than made up for that by hiring more people than what was lost – and the part-timer had greater flexibility in the hours worked – the full-timer has opportunity for advancement that were not available through family-owned stores.  When was the last time a store owner promoted a talented, ambitious person over his son?

I have never understood the resistance to a retailer like Walmart, which achieved its success through competing for the hearts, minds and wallets of the consumer.  And it must still compete today or go the way of Sears.  The consumer is always the winner and should always foremost in the minds of the political elite.

Should these elitists have their way and force Walmart to change its model in any or all the points above then the inevitable result will be higher prices to the consumer.  Essentially – a hidden tax to protect constituent groups these politicians depend on for power.

Why is this important to category managers and sales analysts?  When the retailer you partner with is arbitrarily blocked from entering certain “political zones” you have fewer outlets through which to efficiently distribute your product.

The bottom line is – your brand loses – the retailer loses – and most importantly – the consumer loses through higher prices and fewer choices.

And that’s just my opinion.


Source:  NYC Shoppers (Still) Want Walmart





Top 3 Nuggets Buried In Your Retail Transaction Data

  1. What is selling – and where:  With POS data available daily waiting once a week to adjust store inventory is over.  Immediate shelf adjustments puts the right product in the right place.
  2. Customer buying patterns:  Patterns emerge from data about customer behavior and CPG companies can meet consumer needs before the consumer is aware of those needs.
  3. Is your data clean?:  Pulling in structured data into rigidly structured DSR data warehouses is fairly straight forward.  The retailer and CPG firm share and use the same definition for key retail elements.  But as CPG adopts big data technology that allows ad hoc, sometimes unstructured data to become part of the analytics pool, CPG may find that the category managers and home office are using different definitions for sale, customer, etc.  With flexibility comes responsibility – the responsibility of creating a single definition for common retail elements.  Big data allows CPG the flexibility to do this.

To summarize – many nuggets can be mined from the transactional data received from the retailer.  But it is increasingly critical that this data is brought in and analyzed much faster than before.  Big, rigid data warehouses bog down loading increasing volumes of data making it more difficult for CPG category managers, supply chain and manufacturing to respond quickly to changing consumer buying behavior.  Big data, by design, can reduce this process from many hours to mere minutes.

To understand how fast analytical insights can help you gain that competitive advantage for your brand contact us today for a complementary consultation.  (We won’t tell your IT director if you don’t.)



Source:  Consumer-packaged goods sector digs into transaction data








Lessons #CPG Companies Can Take From The 2015 #BackToSchool Campaign

Recent, well respected, retail analysis reports focused on back-to-school campaigns, the second busiest retail period of the year, shows new and emerging trends in customer shopping behavior. These trends will certainly change how retailers approach this sales period.

Some very interesting trends have surfaced and we’ll look at a few below that are gleaned from the annual Deloitte “Back-to-School” survey.

What lessons can CPG brand marketers learn from emerging customer shopping behaviors and expectations? Many, to be sure, so let’s take a look at the trends that can also impact CPG going forward.

  • Shoppers who are mobile savvy may be doing more research on the beach before hitting the stores.
  • Consumers are no longer exclusively driven by discounts.
  • Consumers will be “mission-driven” and making most of the purchasing decisions prior to the store, with digital devices in greater play.
  • This year shows a 6-percent jump in smartphone owners using devices for shopping, with 80 percent of shoppers taking that approach.
  • More than half, 51 percent, of shoppers are not familiar with in-store beacon technology, and 32 percent said they had no plans to use it.

What jumps out of this survey how the use of technology, especially mobile, in shopping is becoming the norm. 80% of shoppers using mobile devices for shopping will only increase as Millennials marry and begin having children.

As retailers continue to adopt technology to market to the individual shopper (e.g. beacon technology) new streams of data are now available to analyze by CPG brands for shaping marketing campaigns. This new data breaks the existing DSRs that many CPG companies use to analyze retail data. It takes, literally, months or years to incorporate new data sets into a rigid DSR data warehouse.

Big data thrives on new, different and unstructured data – because of its design. That’s why Big Data is such a Big Deal in CPG marketing.

Contact us today for a complimentary consultation on how big data can become your big deal.


Source: Back-to-School: Reports reveal what’s hot, what’s not and consumer trends






#PredictiveAnalytics is Really ‘What is the #BuyersIntent’?. Lessons for #CPGMarketing.

Big data and analytics have become the Holy Grail of marketing speak. Being more data driven has definitely become hip, but it’s not hype. Brands and marketers are using data to track customer journeys, to target and capture new customers, and to retain existing ones. Today’s consumers have come to expect a lot more from brands than simply the ability to make a purchase from them. They are looking for greater levels of interaction, better products, and faster and more responsive services. Big data can help brands deliver on these customer expectations. How? By offering rich insights that can enable brands to reach the right people with the right message for maximum impact.

So starts this article in Forbes describing how big data can help CPG companies learn how to reach new (and existing) customers by learning to use predictive analytics to gauge the buyer’s intent.

Existing DSRs, using POS and inventory data, can only tell you what the consumer has done in the past.   It’s exponentially easier to see what buyers have done (in the past) than to predict what buyers will do in the future. Predicting is what we all want to be doing—so that we can anticipate what consumers want—perhaps even before they realize they want it themselves! This is where intent data comes in.

What Is Intent Data?

People leave behind crumbs of behavioral information every time they search the internet. Relevant bits of this info can be pieced together to gain insight into the intent of a buyer. This is intent data. Simply put, it’s information that tells you when a customer is ready to make a purchase. Now, intent-based marketing is nothing new. Think about cookie-based ads, Web analytics or marketing automation—we’ve been using these tools in marketing and ad targeting for years.

Are We Fully-Equipped To Leverage Intent Data?

The right use of intent data can definitely take personalized marketing to a whole new level. It can open windows to the buyer’s mind in a way we’ve never seen before. But the question remains, are we there yet in terms of measuring buyer intent?

recent study by Forrester found that 78% of surveyed marketers believe using intent data can lead to better ad relevancy, and 67% think it could help them gain a competitive edge. However, inaccurate data (57%), inability to combine first and third-party data (49%), and not knowing how to feed intent data into targeting technology (54%) were cited as some of the biggest roadblocks of using intent data to reveal desired insights. Plus, the basic shortcomings, such as lack of proper technologies and limited human resources, indicate that marketers may not be fully equipped to benefit from intent-based targeting just yet.

I think we need to first overcome the basic challenges of capturing and making sense of the right data before we can use it to understand buyer intent—which for now, remains more or less a nebulous thing.

What is the Bottom Line for CPG Companies and CPG Marketers?

Using all the data that is available to you – from retailer supplied POS/Inventory data to other unstructured and “ad-hoc” data that can come from a category manager’s spreadsheet or from survey data from the internet. The trick is to have the right technology to bring in disparate data and often unstructured data to gain insights right now.

If you are tired of your old DSR company telling you it will be ‘next year’ before they can bring in your “unconventional data” – then you need another BI company. One that is built off of modern big data technology that allows you to incorporate new and ‘unstructured’ data in days not weeks, not ‘next year’ to gain insights into what the consumer is thinking now – not a year from now.

For a complementary BI consultation contact us today.


Source:      Can We Really Use Big Data To Measure Buyer Intent?




#CPG: 10 Reasons Why Now Is the Time to Get into #BigData

Rick Delgado is a new technologies freelance writer. In this article he takes an objective view of Big Data and lays out 10 reasons why now is the time for Big Data. My observations are italicized below.

1. It will keep your data secure

Being able to completely map your data out in front of you will make you better at analyzing potential threats. You can easily ensure that the most sensitive data you have in your system has all of the necessary security features it needs to stay well protected and within any sort of regulations that your business has to adhere to.
Many BI tools have provided for this sitting on top of the data – however – the big data structure allows this to be mapped into the clusters where data lives.

2. It opens up brand new revenue sources

You will gather a ton of insight into your part of the market. This insight is valuable, and not just to you. Selling out non-personalized industry data about trends in the market can bring in a ton of money from any other businesses operating in the same portion of the industry that you are, making it a great way to bring in some more funds.
While this is not always possible for a CPG company, for example, to do when retailer-sourced data is in the mix there are other opportunities at the enterprise level.

3. It’ll give you an advantage

Businesses are built on tradition. Any industry is going to have years of tradition that believe that one way of doing things is the right way and if it isn’t broke, don’t fix it. One important value that big data has is that it lets you really examine and analyze preconceived notions about aspects of a business you may have never even considered. It will provide better data when it comes to experimenting and trying to innovate, meaning that you’ll be able to get a much better advantage over your competitors.

4. Better Visuals

Big data requires cutting edge data visualizing tools in order to translate all of those numbers and data points into something a bit more tangible. This will increase overall usability that can be utilized by people in the business themselves or their end users.
There are increasing numbers of tools available for the user to create insight from their data lake – Vortisieze prefers MicroStrategy but ultimately is agnostic toward the BI tool selected giving you maximum flexibility.

5. It’s very easy to set up

Big data used to be something that only big corporations could afford to get into. Luckily, there are alternatives that can bring the benefits of big data to a company of any size. Hadoop is a great open source framework that can handle large amounts of data. Hadoop works with Excel, which most businesses already use.
The entry point is such, especially with the ABC of business (Analytics, Big Data, Cloud Computing), that retailer sales/support offices can easily add this as a budget item without involving their IT division.

6. It helps your business evolve

One of the best things about big data is just how scalable it is. Getting the right tools means being able to convert not just number data, but also text, audio, and video files to find patterns that can give a business a ton of insight into the market. Investing in big data as a small company means you’ll be able to easily handle all the data easily that comes with growth.
You begin seeing your business as your customers (the ones buying your products from the retailer) see your business.

7. It can significantly cut back on maintenance

Businesses that rely on large pieces of equipment often spend tons of money when it comes to replacing and maintaining them using predetermined data that tries to predict how long they’re going to remain efficient. Big data allows you to get rid of rounded averages and replace them with specifics, allowing you to squeeze even more life out of machinery that still has plenty of use left.
And with cloud computing, also called data-as-a-service, there is no equipment involved to maintain.

8. It brings you closer with your customers

The customers of today are a lot different than in the past. The rise of the internet allows them to thoroughly and tirelessly research a product before buying and to communicate with tons of people about which brand they should do business with. Big data allows you to better profile these fickle consumers and figure out specifically what they want.
See comments to #6 above.

9. It’s easier to analyze risk

There’s more to business than running your own company effectively. Every business is just one in a large industry that must regularly compete and innovate in order to stay ahead of the rest. Utilizing big data to analyze things like news articles and social media will give you cutting edge information about the biggest and latest developments in your industry.

10. You’ll be able to improve your products

Big data is a key that’ll explain specifically what your consumers really think about your product. Big data is even being used in medical research for companies that do personalized medicine or companion diagnostics, and need to analyze large amounts of biological data. You’ll be able to use your insight to easily get a better picture of your customers based out of different geographic areas and belonging to different demographic groups. Once you’ve seen how the product is perceived, you can easily raise efficiencies in key areas along the product process.
These are extremely valuable insights to present to your retailer buyer – enabling your company to rise above the noise from your competition.


Source:  10 Reasons Why Now Is the Time to Get into Big Data





Getting Started with #BigDataAsAService #CPGMarketing

Good Saturday morning. Enjoy your coffee and dive a little deeper into an article I recently found.

Written by Raghu Sowmyanarayanan, a vice president at Accenture, he spells out the major thoughts around what the newest trends in big data for enterprises.

Big-Data-as-a-Service (BDaaS) is an emerging trend with great potential for adoption. We have begun to hear CxOs say that BDaaS makes big data projects viable. We explain why the technology is so appealing.

Mr. Sowmyanarayanan covers these topics in his article and the link to the entire piece is below.

  • What is BDaaS?
  • Is the BDaaS Architecture Rigid?
  • Why BDaaS?
  • Top 3 Myths about Big Data as a Service
  • Myth #1: It is an Infrastructure Play
  • Myth #2: Architecture is Very Complex
  • Myth #3: It is Hard to Implement

Source:  Getting Started with Big-Data-as-a-Service






#CPGMarketing: The Age of #DataObsession

This new era of big data (some say huge data) is being called “The Age of Data Obsession.” Below are a few snippets from the recent Sogeti / Ovum Business Intelligence & Information Management Symposium 2015.

  • Information is a fundamental currency of business created from the raw material of data, and while in recent years that resource has become abundant almost beyond belief, our ability to benefit from this insight has lagged behind. Organizations must therefore scale up their information factory, accelerate their business processes, and become obsessive about applying data to all aspects of their decision-making, or risk becoming noncompetitive and irrelevant in the modern data-driven era.

This is clearly a call to action or fall behind and out of the game.

  • For best-in-class businesses, the obsession with data entails its application to every aspect of their operations, from the optimization of business processes, through to decision support for more complex strategic problems. It involves interrogating as wide a range of sources as possible, both internal and external, structured and unstructured; and of delivering the resulting insight at a speed which can match and ultimately accelerate those operational and decision-making processes. Increasingly this requires real-time or near real-time data analysis and presentation, which has significant implications for the data to insight process.
  • Manipulating data at this speed and scale requires a fundamental change in approach, both in terms of technology, and of the underlying data management processes that are applied. From a platform perspective, we are currently seeing the integration of solutions specialized for particular aspects of data handling and manipulation into a unified architecture, reflecting the need to combine existing data warehouse investments with newer big data systems and analytic databases. Logically however, the change in data analysis goes much further, with a growing design mind-set that mandates a large data lake to which organization is applied only at the point of seeking to answer a question (driven in part by the rapid adoption of in-memory computing).

This new obsession blows away the capabilities of traditional relational database management systems (RDBMS) and is tailor-made for what big data (primarily using Hadoop) can achieve. This is true both in the capability to incorporate unstructured data and rapidly load, process and present that data in insightful ways.
Combined with BI analytics tools harnessing the new technology this data brings power to the decision maker.

  • There is a big caveat here though: however powerful the technology, if the organization does not also upgrade its foundational data management processes and its information management strategy to match, then the outcome will at best be indiscriminate and at worst chaotic. From a strategy perspective, organizations must define their information needs and capabilities in support of business objectives, while data management processes must be sufficiently robust so that insight can be generated from data in a systematic and repeatable fashion.

Source: Sogeti / Ovum Business Intelligence & Information Management Symposium 2015




Reviewing 3 #bigdata types that will increase your #CPGMarketing ROI

After reading the online article – “3 big data types that will increase your ROI” – it struck me as something that CPG companies who sell directly to large retailers sometimes limit their view to the data the retailer provides back to them. Make no mistake – that data is essential to a profitable partnership with the retailer. But with innovations in analytics, big data and cloud computing richer, more robust, datasets can provide a deeper story than POS data alone.
Two of these data types have relevance to how CPG companies interact with their retailer.

Social Data
By now, most companies have some sort of social platform or presence in place. A Facebook page to share content, a LinkedIn group to network with prospects, or perhaps a Pinterest page to showcase products. Many marketers are hyper-focused on measuring the number of followers, retweets or shares their pages and content are getting. This is certainly a good thing to measure and engaging with your customers and prospects on social platforms is a must. However, there are huge opportunities within social media that can lead to even bigger wins.
Knowing this information can increase the value of the analytics you share with your buyer.

Hard to Find Data
Numerous, hard-to-find data assets such as these can be sourced from the big data universe through a data-as-a-service solutions provider. What’s powerful about using a data-as-a-service solutions provider, like Vortisieze, is that that you don’t need to implement a big data system or hire data scientists to start accessing this data. The insights have already been mined and sourced, and can be integrated directly into your database.
For CPG, weather data has been difficult to incorporate into traditional analytics, however, Vortisieze has incorporated this alongside POS, inventory and demographic datasets, just to name a few.

With traditional relational database management systems (RDBMS) adding unstructured datasets is problematic, time consuming and expensive. With Vortisieze as your data-as-a-service solutions provider adding new unstructured data is fast, low-cost and actionable with your retailer.