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Retailers to increase IoT spend fourfold by 2020 to US$2.5bn | #BigData #TechnologyTrendsInRetail

Anticipating the winds of change, major retailers are expected to increase their investment in internet of things (IoT) technology fourfold to US$2.5bn by 2020.

In the commercial space, IoT in retail is one of the clearest examples where connected network technology could have a significant impact on customer interaction in stores.

In particular, retailers have already begun investing in IoT hardware, including Bluetooth beacons and radio frequency ID (RFID) tags that allow them to send information to them in-store and keep a tab on stock and price levels, respectively.
Read more . . .

How will your DSR handle all that new, differently structured data? (Hint – it won’t!)
Contact us today to discover how Vortisieze analytics can bring this, and many more, types of data to your analytics package.

Source: Retailers to increase IoT spend fourfold by 2020 to US$2.5bn

#BigData
#CPG
#CPGMarketing

#TechnologyInRetailIndustry

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#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

 

#AnalyticsInRetail

#CPG

#CPGMarketing

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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.

 

Sources:

Facebook July Leaderboard for CPG Dips and Dressings

http://blogs.imediaconnection.com/blog/2015/08/17/facebook-july-leaderboard-for-cpg-dips-and-dressings/

 

Ranking 25 of the most engaging brands on Facebook

http://zuumsocial.com/ranking-25-of-the-most-engaging-brands-on-facebook/

 

July Ranking of 25 Most Engaging Brands on Facebook

http://zuumsocial.com/july-ranking-of-25-most-engaging-brands-on-facebook/

 

#CPG

#Business Intelligence

#BigData

#AnalyticsInRetail

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Top 3 Roles Required By #CPG Companies for #BigData #Analytics Success

Big data and analytics are at the top of the corporate agenda these days.  While big data and related technologies are relatively new analytics are certainly not new to the CPG category managers and sales analysts on the front line with retailer buyers.  Most CPG companies use some type of analytics to make sense of retailer supplied POS and inventory data.

However, as big data analytics technologies jump front and center ahead of outdated DSR and other data warehouse structured data (read hard to change and easy to break) acceptance by the enterprise, especially those who require the insights in their weekly – if not daily – work with buyers, is essential for success.

Information-management.com published, on Monday, August 10, 2015, a clear and concise explanation of the three essential roles that must be filled by a CPG company to have business analytics success.

  • Suits (consumers of data) – The domain and sector business specialists who have a strong understanding of the organization’s broader business goals and strategy. They use analytics to optimize their business by providing deeper insights and increased efficiencies. They tend to be less focused on the “how” of big data and more focused on the “why.”
  • Math whizzes (producers of data) – The analytics specialists who construct databases, develop analytics scripts / models and design visualizations and dashboards for analytics consumers. They tend to be more focused on crafting the solution using innovative techniques and advanced technology, but generally don’t have as deep of an understanding of the business problem as the suits.
  • Techies (enablers of data) – The architects, who create the infrastructure, configure and implement analytics software, and establish data standards and management procedures. They are focused on enabling the sustainable operation of analytics solutions at an enterprise level, and tend to spend limited time on the specific business analytics solutions.

The article refers to the first role as Suits, invariably meaning upper management, for CPG companies this really means category managers and sales analysts who must gain actionable insight from the analytics.

The other two are more technical in nature – the geeks – typically in the IT departments of major CPG enterprises.  For most ‘suits’ – dealing with IT can be frustrating and painful process.  But it doesn’t have to be that way.

Working with Vortisieze those two roles are fulfilled by our team and technology (big data and cloud computing) and eliminates the need to engage IT at all.  Whew.

To learn more about how Vortisieze can bring you actionable insights better, faster and cheaper (and immensely less painful) contact us today for a complimentary BI consultation.

Even if you are currently with one of the other guys, Vortisieze can show you how to reduce cost of ownership of a BI platform while adding rapid flexibility to add additional streams of (sometimes unplanned) data.

 

Source:  The Three Types of People You Need for Analytics Program Success

 

#CPG

#DataForAnalytics

#DataAnalyticsTechnology

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#Retailing: Target Launches Beacon Test In 50 Stores – #TechnologyInRetailIndustry

 

Target, the second largest general merchandise retailer in the U.S., announced this morning that it will start testing beacon technology in 50 of its stores nationwide. With beacon technology, the company says it will be able to send information about deals as well as recommendations directly to consumers’ smartphones, provided they opt in to receive these alerts.

 

Initially, the beacon technology will work with those users who have the latest version of the Target iPhone app installed on their phones and have Bluetooth turned on.

Techcrunch.com is reporting this in an online article published on August 5, 2015.

Beacon technology is emerging as the newest way to technologically engage the consumer.  As you read the article you will probably begin thinking of new ways to promote your brand in partnership with the retailer.  Especially when the retailer begins to tie the recipient of the beacon to the POS at the cash register.

And – assuming retailers will make this data available to vendors and suppliers – this will provide a way to draw new insights into the consumer.  However, using an old-style data warehouse can slow the availability of these analytics because it requires a lot of planning and work to add a new data source to an existing DSR (demand sensing repository).

One of the benefits of the “big data” trend is the ability to bring in any data source – structured or unstructured – without impacting the existing data.  New data sources added within hours or days, not months or years.

Imagine designing a promotion that specially targets those who have demonstrated tendencies to purchase similar products (perhaps from your brand competitors) and pulling those consumers into your brand family.

It opens a new world in retailing and begins to level the playing field between brick-and-mortar and online retailers who have used similar techniques online through collecting the browsing and purchase history of consumers.

This is only useful when the data is available to the analytics engine to provide you meaningful insights to share with your buyer.  Big data technologies provide the ability to have new data & analytics delivered to you for insightful action.

Contact us today for a complimentary consultation.

 

Source:  Target Launches Beacon Test In 50 Stores

#TechnologyInRetailIndustry

 

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#BigData and the 2016 Presidential Election #PredictiveAnalytics

What Nate Silver did for President Obama in the 2008 election cycle Deep Root Analytics, a media analytics company formed in response to the 2012 Republican loss in the presidential election, is working to do for several Republican candidates in this election cycle.

Deep Root Analytics partners with data-blending and advanced-analytics company Alteryx to merge voter file information, set-top box data and commercial data to optimize audience targeting and TV ad-space buying.

While this is very interesting to observe ultimately we in the retail space must learn from the lessons that these, and other big data exercises, provide.  As consumers move from one retail channel to another (actually many) channel using all the data available is paramount.  No longer will solely relying on the POS/Inventory data your retailer provides you be enough.

Wondering how to make this all come together for you?  Contact us today for a complimentary consultation.  And enjoy this election as you watch others use big data to move their candidate (brand) forward in the voter’s (consumer) eye.

 

Source:  How Data and Programmatic TV Will Dominate the 2016 Presidential Campaign

#DataForAnalytics

#DataAnalyticsTechnology

#PredictiveAnalytics

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#Walmart: The Big Data Skills Crisis And Recruiting #BusinessAnalytics Talent

As the amount of digital information generated by businesses and organizations continues to grow exponentially, a challenge –or as some have put it, a crisis–has developed.

There just aren’t enough people with the required skills to analyze and interpret this information–transforming it from raw numerical (or other) data into actionable insights – the ultimate aim of any Big Data-driven initiative.

One survey recently carried out by researchers at Gartner IT +0.93% found that more than half of the business leaders they queried felt their ability to carry out analytics was restricted by the difficulty in finding the right talent.

Overcoming this problem is a challenge that all companies will have to face, and market leaders–aware that they have more to lose than many by falling behind in the race to keep up with technology–have come up with some innovative solutions.

Walmart decided to apply one of the fundamental weapons in the Big Data arsenal–crowdsourcing–to the problem, with positive results.

Last year, they turned to crowdsourced analytics competition platform Kaggle. At Kaggle, an army of “armchair data scientists” apply their skills to analytical problems submitted by companies, with the designer of the best solution being rewarded – sometimes financially, in this case with a job.

To continue reading click the source link below.

 

Source: Walmart: The Big Data Skills Crisis And Recruiting Analytics Talent

 

 

#DataForAnalytics

#DataAndAnalytics

#BigData

 

 

 

 

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#DataAndAnalytics:  From #BusinessInsights To Value

D&A is rising up the agenda – for executives, for business managers, for customers and, increasingly, for equity markets and investors. And now, more than ever before, organizations are starting to sharpen their focus on driving value from their D&A investments. And as organizations move along the journey from data to insights and from insights to value, key themes are emerging.

Go to the article (link below) to read a couple of good reports regarding data & analytics.

Source: Data & Analytics: From insights to value

 

 

#DataForAnalytics

#DataAndAnalytics

 

 

 

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#DataForAnalytics: #PredictiveAnalytics tools point to better business actions

From recommending additional purchases based on the items that customers place in online shopping carts to pinpointing hospital patients who have a greater risk of readmission, the use of predictive analytics tools and techniques is enabling organizations to tap their collections of data to predict future business outcomes — if the process is managed properly.

Using predictive analytics tools lets organizations look ahead in an effort to optimize business strategies. But there has to be a purpose to the analytics efforts, and a solid plan behind them.

Predictive analytics has become an increasingly hot topic in analytics circles as more people realize that predictive modeling of customer behavior and business scenarios is “the big way to get big value out of data,” said Mike Gualtieri, an analyst at Forrester Research Inc. As a result, predictive analytics deployments are gaining momentum, according to Gualtieri, who said that he has seen an increase in adoption levels from about 20% in 2012 to “the mid- to high-30% range” now.

That’s still relatively low — which creates even bigger potential business benefits for organizations that have invested in predictive analytics software. If a company’s competitors aren’t doing predictive analytics, it has “a great opportunity to get ahead,” Gualtieri said.

Predictive analytics projects can also provide those benefits across various industries, said Eric King, president and founder of The Modeling Agency LLC, an analytics consulting and training services firm based in Pittsburgh. “Everyone is overwhelmed with data and starving for information,” King noted.

But that doesn’t mean it’s just a matter of rolling out the technology and letting analytics teams play around with data. When predictive analytics is done well, the business benefits can be substantial — but there are “some mainly strategic pitfalls” to watch out for, King said. “Many companies are doing analytics to do analytics, and they aren’t pursuing analytics that are measurable, purposeful, accountable and understandable by leadership.”

Data scientists don’t know it all

Plan ahead on predictive analytics

For a free consultation on your business intelligence strategy contact us.

 

 

Source: Predictive analytics tools point to better business actions

 

 

#DataForAnalytics

#PredictiveAnalytics

#BigData

 

 

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#DataAndAnalytics – Why are #BusinessIntelligence Professionals Missing the Boat

A recent online article in the data & analytics arena talks about business intelligence professionals who describe their job as 90% cleaning data.

While this isn’t a big deal to you as category manager or sales analyst working for a CPG supplier to a large retailer – it affects you every day in how your data for analysis is delivered and presented to you.

“Reformatting, cleansing and consolidating large volumes of data from multiple sources can be overwhelming,” Yaniv Mor, CEO and co-founder of Xplenty, said. “BI professionals are still struggling with the best approach to shorten the time between integration and analytics. As a result, businesses are often slow to unlock their data’s true potential for revenue or operational improvements.”

This process is called ETL (for Extract, Transform, and Load) and while slight majority of BI performs this locally, 49% are using cloud services for this.

You may be asking “so what?”

The so-what is when choosing a BI, or data-as-a-service, provider you may want to consider one that uses technology that 1) delivers your insights on-time, 2) is designed for rapid ETL with disparate data, and 3) gives you control over what you want to see.

One such technology is using big data (Hadoop) in the cloud, which is exactly what we at Vortisieze use to deliver the right insights at the right time.

Give us a call or click here to contact us.

#DataAndAnalytics

#BusinessIntelligence

#DataForAnalytics