Why? Let’s start with the facts:

1. NielsenIQ is the industry leader in fast-moving consumer goods and market data. If you want to know what shoppers are doing, NielsenIQ offers the best source of information.
2. AnswerRocket, similarly, is the industry leader in AI-powered data analysis. If you want to automate the process of getting deeper insights into your data, AnswerRocket can do just that.
3. The NielsenIQ Partner Network builds connections between Nielsen and companies servicing the CPG and retail industries. If you want open collaboration between NielsenIQ’s expansive data and top-of-the-line analytics tools, the NielsenIQ Partner Network can facilitate those conversations.

That’s why this partnership is great; everyone involved is bringing incredible resources, insights, and aspirations to the table.

Our partnership is especially timely, given the current landscape for leading consumer goods manufacturers.

To stay competitive, CPGs need to identify growth opportunities and keep a handle on consumers, brands, competitors, and the market.

Here’s how AnswerRocket’s collaboration with Nielsen can empower CPGs to do just that.

How the NielsenIQ partnership impacts CPGs

AnswerRocket customers now have streamlined access to NielsenIQ data, which means better, more comprehensive market analysis within seconds.

Plus, with NielsenIQ’s industry expertise and AnswerRocket’s AI-powered insights, it’s faster and easier than ever before to see what this data actually means and go beyond surface-level analysis.

Don’t just know that sales are down in the Southeast. Know how your sales compare to the general health of the region’s market. Then drill in to determine which brands, SKUs, stores, and more are contributing to this dip. Let our machine learning insights pinpoint exactly where your opportunities lie.

Are you following marketplace trends? Are there any notable deviations? With NielsenIQ’s data, you can put your analytics into the right context and see how you stack up against the market.

With AnswerRocket’s intuitive interface, everyone from your CMO to data analysts to brand and category managers can get their questions answered in seconds. Ask:

• How did Brand X perform last month?
• What is the market penetration for Brand X by month?

Key players can make decisions faster and with more information than ever before.

So the NielsenIQ Partner Network is great for business, and ultimately, the bottom line. But let’s broaden the context. What does the NielsenIQ Partner Network mean for the future of analytics?

How the NielsenIQ Connect Partner Network impacts CPG data

The NielsenIQ Partner Network is designed to combine the power of raw data with the innovation of modern AI-driven analytics tools. In doing so, the NielsenIQ Partner Network breaks down the typical barriers that:

1. Keep valuable data out of reach for the businesses that need it.
2. Slow down data analysis with an inefficient, labor-intensive process.

In other words, the NielsenIQ Partner Network is creating a system where data flows seamlessly between NielsenIQ clients and partners — all for the benefit of the end user.

Bridging the gaps between information and insights empowers business people to enjoy a streamlined pathway from questions to results. Employees such as your marketing team members, who really need to know the nitty-gritty details of your sales figures on a constant, rolling basis can get those figures whenever they need them.

Putting powerful data in the hands of the people who can use it most is important to us. By removing barriers to insights, the Connect Partner Network shares our goal. We’re committed to providing even more value with better data and incredible insights that can shape the future of your business.

Ready to see AnswerRocket in action? Learn how AnswerRocket leverages data like NielsenIQ’s to produce powerful insights into your business and industry. Get started with a demo today.

The post We’re Excited to Join the NielsenIQ Partner Network first appeared on AnswerRocket.

But I was also intrigued why Gartner recognizes Cool Vendors. I love the association – but I wondered why the Gartner analysts landed on that particular adjective.

I gained some insights by reading a Gartner article about their selection guidelines for Cool Vendors. They defined Cool Vendors as emerging companies that shared three qualities:

1. Innovative — enables users to do things they couldn’t do before.
2. Impactful — has or will have a business impact, not just technology for its own sake.
3. Intriguing — has caught Gartner’s interest during the past six months.

With those criteria, I understood better what Gartner saw in AnswerRocket. Here’s how I think we check each of those boxes:

Innovative
Analytics software has been around for decades. The problem is that these software packages were designed for technical analysts who write SQL and understand database schemas. In today’s data-driven business environment, these specialists can no longer keep up with the data and analytics needs of business users. Many of these traditional BI solutions tried to solve this by extending their reach from technical specialists to business users – but these tools are just too complex.

AnswerRocket was built from the ground up as a self-service analytics tool for non-technical business users. This was the persona we focus on, versus more technical users who are comfortable handling raw data. We provide an interface they use every day: a search box that accepts natural language questions and returns answers in seconds.

That’s pretty innovative – but we aren’t stopping there. Our Smart Briefing gives an executive-level view of your business with automatically generated charts and natural-language-generated insights. This leaps past the KPI dashboards of today, by alerting business leaders to trends in their data, identifying outliers, and reporting progress against goals in easy-to-digest articles generated by the system.

Impactful
One of the best parts of my job is hearing about the positive difference we’re making for our customers. AnswerRocket delivers significant bottom-line impact – in fact, some of our customers experience an ROI within a few weeks of implementing AnswerRocket.

Check out SnapAV’s experience of finding a $1M opportunity within just a few minutes of reviewing their data. Or listen to how AnswerRocket delivered groundbreaking analytics to the game designers and marketers of Hi-Rez Studios.

Intriguing
Gartner’s annual Data & Analytics Summit brings together all of the key players in this space, along with thousands of enterprise leaders looking for analytics solutions. We were honored that Gartner asked us to help kick off the Summit by giving a demonstration of AnswerRocket at their Innovative BI in Analytics session. Our smart data discovery solution clearly struck a nerve, as our booth was packed the rest of the Summit with people wanting to learn more.

I give demos of AnswerRocket every week, and I regularly get astonished reactions when people see our analytics tool for the first time. It seems too good to be true – until they see how quickly we can take their data and allow them to get answers and insights in seconds.

Being named a Cool Vendor is certainly cool. But we’re not going to rest on our laurels. We remain even more committed to deliver innovative solutions designed to positively impact our customers and intrigue those seeking analytics solutions.

The post It’s Cool That Gartner Thinks AnswerRocket is a Cool Vendor first appeared on AnswerRocket.

Alan Turing (you know, the guy who decided computers only needed 0s and 1s) thought that the ultimate test of a machine’s intelligence is whether it can hold a conversation with a person. If the machine has intelligence, the person will be fooled into believing that a human mind is on the other side of the dialogue.

According to Turing, mastery of language is intelligence. Since Turing’s time, the idea has been researched and extended by other scholars. The test has been attempted, and algorithms have passed limited forms of it (see Eugene Goostman). But every time a computer passes the test, the results are challenged and the test is made more difficult. Researchers are egging each other on to push the boundary further and further toward a machine that understands the thoughts of a mind. Conceptually, the bar could be pushed high enough that some humans would not pass! At least that’s the pattern we have seen with other AI developments like games and handwriting.

In contrast, consumers now have the commonplace experience of posing natural language questions to machines, including Amazon’s Alexa or Amy from x.ai. Far from the esoteric idea of machine minds that might one day “talk back,” businesses are focused on that evergreen consumer desire: convenience. Product announcements in the area of linguistic user experience – LUX, to coin a phrase – are now a weekly event. As much as we love our web browsers and smartphones, it turns out we’d rather use words than buttons. And while it’s fun to tease Siri into an amusing retort, Siri is really a productivity application that’s there to get something done for us.

The disparity between the Turing test and commercial practicality could be another example of the bumblebee buzzing around while scientists at the whiteboard prove it can’t fly. In Turing’s test, the machine proves that it is intelligent by responding to a human mind through language. That’s because when Turing formulated the test 12 U.S. presidents ago, the idea of ordering a pizza online had not occurred to anyone (well, maybe Nikola Tesla). Arguably, performing the right task as requested is a great way to know that the machine “understands.” We’ve all had conversations with people that definitely didn’t reveal any intelligence, and there have been plenty of times when software did something we found delightfully clever!

Like any new technology, LUX applications began by providing a better way to do something we could already do. Digital assistants that take dictation or set appointments are nice. Wolfram Alpha promised to “understand” our questions, and it is an amazing piece of work. But these early steps don’t mean that the tech will take off. Remember Graffiti on the Palm Pilot? Some great tools are nonetheless a dead end.

LUX needs to pass the next threshold to change the future: Language has to allow systems to do something new. The killer app remains on the loose. Convenience and speed are enough to win the consumer market, but business won’t tip to LUX until these new systems provide capabilities outside of merely activating on keywords.

What’s interesting about LUX is that there is already an existence proof for the killer app. We speak to each other every day using our evolutionary wetware and creating great business value. Language is effective. If systems could understand what we say, we could cut costs and improve efficiency by transferring intent directly into the systems that implement it. Sort of like, “Alexa, order me a pizza,” writ large. Imagine, “Alexa, increase profits in the paper division.” People can’t be cut out of the system because they originate the intent, but LUX implements it at the speed of thought. FastCompany recently profiled the business chatbot phenomenon. A number of companies, including my own AnswerRocket, are applying LUX to business intelligence. The list goes on.

Philosophers can argue about what makes intelligence and the nature of “mind.” In the meantime, LUX-enabled software will continue to proliferate, even as it sometimes makes comical mistakes like Alexa’s responding to its own TV commercials, or Siri’s injecting an answer at a White House press conference. Iterations and innovations will improve the technology until it takes its place in the arsenal of systems that improve our lives. Like the stray dogs that ride subways in Moscow, we don’t have to understand how it works to embrace and enjoy it. Our only mistake would be to underestimate what’s possible and not to prepare for what’s next.

Continued Reading

Natural Language & Analytics: A Cheat Sheet for Business People — Now that you have learned the larger context behind AI and the evolution of natural language computing, it’s time to dive into how natural language factors into the business world. More specifically, this comprehensive web page covers the scope of natural language possibilities in the analytics space.

Ian Lamont CC BY

The post AI and the Evolution of Natural Language Computing first appeared on AnswerRocket.

In Habit 2: Begin with the End in Mind, Covey says, “If the ladder is not leaning against the right wall, every step we take just gets us to the wrong place faster.” That analogy helps me check not just what I’m doing, but why I’m doing it in the first place. Is my ladder leaning against the right wall?

Those of you in digital marketing are probably ready to do the same thing. After laser focusing on holiday performance, it’s now time to look at the big picture.

A 2015 Gartner study of CMOs found marketing budgets grew 10% in 2015. And 2/3rds of respondents expected their budgets to grow even more in 2016. These trends have continued as marketing, especially digital marketing, has gained more prevalence and potential for higher ROIs.

As such, a lot of time and money goes toward marketing execution – the keyword lists, the campaign creative, the ad placements.

But without the right analysis, you’re sunk. In a recent Forbes Insight study about data-driven digital marketing, 72% of respondents said their organization was more focused on knowledge gathering than acting upon their data.

Take a moment and evaluate where your team’s ladder is leaning.

If the ladder is not leaning against the right wall, every step we take just gets us to the wrong place faster.
– Stephen R. Covey

• Is it time to revisit our mission statement? These can get overlooked and stale in the crunch of day-to-day operations. Define this correctly, and you’ll get everybody in the same mindset. Ask yourself: What are you trying to achieve? Maybe you aspire to more than simply hitting top-line goals. Maybe you aspire to attract more of the right customers. More satisfied ones. Raving fans, even.
• What metrics are most meaningful to us? You’ve got the main ones covered: sales, retention, satisfaction, ROI. But what are the lower-level metrics that are your leading indicators of future success? Which metrics will most drive your mission?
• How can we get the data? Starting now, you shouldn’t deploy any digital marketing that isn’t trackable. All of this data should be easily and immediately available to your team.
• Do we have the right tools? With all of this data you’re accumulating, you’ll need an easy and fast way to analyze your business trends and opportunities. A solution like AnswerRocket provides self-service analytics without any technical involvement. You’ve got the simplicity of a Google™ like search with data shown immediately in charts, graphs, and maps.
• What does success look like? It’s probably time to redefine your goals and targets. Digital trends are changing rapidly. See HubSpot’s Ultimate List of Marketing Statistics from 2018 to make sure your objectives are current.

Unlike marketing strategies of the past, it’s not enough to define metrics once. If you’re truly studying your data, you’re going to have a lot of additional questions to explore. The answers to those questions will help you not just shift your tactics but also ensure your ladder is leaning against the right wall.

Photo by Sophie & Cie CC BY

The post Your Digital Marketing Mission first appeared on AnswerRocket.

And it’s more than just lip service. More than half of the respondents said they plan to invest from $25M to $100M in data analytics over the next two years.

How do these leaders from retail, advertising, media, and more think that money should be spent? 31% of respondents answered “technology.” That’s a broad category that covers state-of-the-art systems and tools to collect, synthesize, and interpret your data.

But executives put an even greater emphasis on people. 69% said their top priority was one of three personnel-related topics:

• Organizational structure (30%)
• Culture (20%)
• Talent (19%)

Credit: Forbes Insight

So now that you have executive expectations and budget. How exactly will you build a best-in-class data-driven digital marketing team?

1. Recruit those with top-notch skills. Kellogg’s School of Business offers great tips on how to attract – and then keep – these big data experts.
2. Train those you already have. Help your team grow their analytical skills with the following resources:
   • Courses – The University of Illinois offers a 6-course digital marketing certification via Coursera. For a reasonable price, your team members can learn the latest digital analytics theory and practices.
   • Blogs/newsletters – There are tons of great options, but try Blue Fountain Media’s The 10 Best Digital Marketing Blogs You Should be Reading.
   • Books – Need something to read over the holidays (or maybe even gift ideas)? Check out Keeping Up with the Quants: Your Guide to Understanding and Using Analytics by Thomas H. Davenport and Jinho Kim.
   • Conferences – Now’s the time to plan your budget for travel and training. Kristi Hines has compiled a list of more than 250 business and digital marketing conferences. Who knows – maybe our paths will cross at one or more of these.
3. Create a Data-Driven Culture. What exactly does that mean? Chief Marketer gives suggestions on how to grow a team environment that embraces business intelligence. (Hint: It’s not about the technology.)
4. Give them tools that make it easy to do the work. It’s hard to transform a marketer into a data scientist – and frankly, probably not a great idea. But give your team user-friendly analytics tools, and they can much more quickly optimize your digital marketing spend without having to wait for IT. This should make for a much happier and more profitable year

Photo by Gary Knight CC BY

The post Data-Driven Marketing: 4 Ways To Build Your Team first appeared on AnswerRocket.

Jet Ski on Your Data Lake – Natural Language Query on Hadoop from Pete Reilly on 

The growth of big data has created a whole new set of challenges. Namely, the ability for expanding groups of users to leverage this data to drive profitable action. Self-service analytics has been talked about for decades, but only a handful of technicians in each company can use the current generation of data exploration and visualization tools to create new visualizations and insights.

In this talk at Strata + Hadoop World in New York City, Mike Finley discusses the advent of big data and the changes needed to empower business users with self-service analytics using natural language search on big data. Mike shows a demo of AnswerRocket using retail data and natural language search to make big data discovery accessible to the everyday business user.

The post Natural Language Search on Retail Big Data first appeared on AnswerRocket.

Business intelligence adoption has struggled to get past 25 percent. The arena of workforce management is no different and has likely lagged behind even these statistics. Companies have struggled with traditional business intelligence tools like Microstrategy and Business Objects to answer questions like:

• “how many early in and late out exceptions occurred over the last year?”
• “what is the rounding rule net difference at plant x from march to may?”
• “How many employees with early in or late out exceptions incurred unscheduled overtime?”

Can you answer these questions on a traditional reporting or dashboard tool? Perhaps, but at best, it’s a bit like playing a game of jeopardy. You get a board full of answers and have to guess the question.

At worst, the answer to your question hasn’t been anticipated and, as is often the case with workforce-related questions, the user is left to file their request with IT. And wait.

We think there’s a better way. Google, Apple, and Amazon have trained us as consumers to expect a simple, fast, even elegant consumer experience. And we now rightly expect that same experience from enterprise software.

AnswerRocket provides search-driven analytics to empower users with Google™ like access to data. Instead of having to file a request with IT, AnswerRocket allows users to simply ask their question. AnswerRocket understands their natural language query, finds the data and presents a visualization any user can understand.

To create this demonstration, we partnered with Workforce Insight, a leading provider of workforce management implementation and analytics services. We are grateful to them for providing us with sample data and insights as to the types of challenges facing workforce managers every day.

The post Search-Driven Analytics for Workforce Management first appeared on AnswerRocket.

AnswerRocket enables self service big data exploration and visualization.

Despite the proliferation of self service analytics tools, enterprises still struggle with democratizing their data. To answer unanticipated questions, users must enlist the help of technical resources. And wait. We think there is a better way.

AnswerRocket empowers people to access their enterprise data without technical help. AnswerRocket provides this Google™-like, search-driven analytics experience by converting natural language questions into queries against Apache Drill, Spark SQL, SAP HANA, Amazon RedShift and many other sources. AnswerRocket answers these questions with visualizations any business user can understand, explore, and share. Without waiting.

The post Natural Language Data Discovery and Visualization first appeared on AnswerRocket.