by scott.gillum | Mar 6, 2014 | 2014, Tech Trends
I had a dream last night that I was hiking along a stream with my family. The same path we’ve hiked and geocached dozens of times. Except this time, Siri’s voice interrupted our hike and asked if we’d like to play a game.
An app I had downloaded came on, and using GPS, our hiking history, and topographical maps of the area, had created a real time obstacle course, complete with the map, times to achieve, and “land mine” rocks to avoid. The “App” had proactively invaded our routine hike by creating a totally new experience.
When I awoke I wondered if I had read this, or if it was truly a dream. Concluding that it was a dream, I knew the article that helped to “inspire” it, and perhaps, playing a little too much Candy Crush may have lead to the creation of the “land mines”.
Earlier in the week, I had read about fitness apps that, for the first time, were positively impacting behaviors. I thought it was noteworthy because even with time spent on mobile devices continuing to grow, we have not invited them into our lives as an active participant, although my teenager may disagree with me. In 2013, Gartner reported consumers spent an average of 2 hours and 28 minutes per day on devices (phone and tablet), and 80% of that time spent inside apps.
Apps have been in “ondemand” mode waiting for us to engage. They haven’t been invited “in” because, for the most part, they haven’t been smart enough to provide us with value. With the era of the “internet of everything” we are entering a new world of connectedness. With devices able to communicate with each other, and soon apps, is this the beginning of new phase of app development?
An era that goes beyond the first generation of “dumb” apps, similar to “dumb terminals” of yesteryear, in that they, with a few exceptions, mostly games, are nothing more than version of existing websites that have been optimized for mobile devices.
Next generation “smart” apps will have the potential to become an active part of our lives by tracking, and understanding our unique behaviors and habits, to creative highly personalized recommendations and experiences. But by 2017, Gartner predicts that mobile apps will have been downloaded more than 268 billion times, and mobile users will provide personalized data streams to more than 100 apps and service every day
Our mobile devices, which many of us carry 24/7, can remember where we’ve been, what we’ve done, and when we did it. They can listen in on our conversations, as we’ve learned, and can access data we have stored on the device and in the cloud.
As a result, be on the watch for the following in the near future:
- The emergence of “small data” – the value and functionality of your mobile device will shift from connectivity to data capture and transfer. In a sense, your phone will act as your own “black box” recording your daily activity, similar to a flight recorder. Apple and Google have the ability to track activity across devices so that most of your waken hours will be captured.
- A “listening” mode on your phone – it already exists the difference is that it will be a setting you control (instead of others). This will add a layer of richness to the data that is already being collected and enable apps to pick their spots to intervene with information, recommendation, etc.
- Highly personalized experiences – apps will leverage multiple sources of data and with artificial intelligence begin to create experiences and recommendations in real time, much of it designed around our daily lives and routines.
- Intelligent Ads – yes, someone has to pay for the free apps and advertisers will be at the ready. As the apps get smarter, so will marketers! Ads will appear at the right time, with relevant offers based on your interest, past buying behavior, and preferences. Some will be rewards based on certain behaviors, and other offers will incent them.
Signs of these types of apps are starting to appear. Apps like the Sleep Cycle alarm clock, that gently wakes you by analyzing your sleep patterns. Using your iPhone as an accelerometer, Sleep Cycle monitors your movement to determine which sleep phase you are in (see the image on the right). Once learned, the phone alarm then wakes you with soothing sounds in your lightest sleep phase.
Think of the convenience of having an app on your phone listen in on conversations when you’re traveling abroad and translate, in real time, in the dialect of that region. Or, as in my dream, the value of taking a routine outing and creating a totally new and highly engaging experience.
Of course progress comes with a cost. Increasing the availability of personal data also increases the threat of those who would like to get their hands on it. In fact, it will slow the progress of this smart app generation. That said, we will see improved security built into devices, and hopefully, there will be “an app for that” as well.
by scott.gillum | Sep 27, 2012 | 2011, Marketing
Original posted on Forbes July 25, 2011
Years ago some colleagues of mine built what we thought at the time was the “holy grail” of business marketing: A sophisticated analytical tool that could tell a marketer where to invest, why, and what the return would be in sales productivity. It could also tell them where to cut dollars, why and what the impact would be on the business.
It was an incredible feat of analytical modeling and technology. Built for one of the most respected and well known companies in the world, so the CMO could answer with absolute certainty the CEO’s question: “What am I getting for my marketing spend?” We thought that it was our ticket to the big time and the rocket to ride to explosive growth, but that was not the case.
It turned out to be the only one we sold. And that always baffled me. Anyone who saw the tool was awed by its power and insight, but they didn’t buy.
Over the years, I picked up some clues as to why others would not buy:
- The head of a major west coast based IT company warned us that our business intelligence tool and analytic model might limit his managers’ ability to make decisions based on their experience … “gut feel.”
- The CMO of a global software company was concerned that our meticulously designed marketing processes, with stage gates and Gantt charts might limit his team’s creativity.
- The head of marketing finance at a major Financial Service company told me that every year they run their marketing optimization model and it tells them that they overspend on TV, and under spend in print. But at the end of the year if there was additional budget leftover the CMO puts it in TV.
I’ve now been able to put the pieces together. I came from a marketing science world and have since learned to appreciate and understand the value of the art of marketing.
Data and analytics can tell you where customers are, what they look like, what they’re interested in, but science alone can’t make customers buy. It can’t make customers advocate for a brand, and it can’t make the hair stand up on the back of their necks.
Insightful, creative and relevant ideas that trigger human emotions can – and do – sell. For as much as I wanted to believe that buyers were rational creatures behaving in predictable patterns, I now understand that they are not.
Marketing, as much as we want it to be, is not an exact science. Technology innovation has allowed us to better understand buyers, influencers and the performance of our activities.
But at the end of the day, business is personal. We can’t remove the human element from the buyer or seller side. Relationships and perceptions matter, how a product and/or a brand makes a customer feel is important, and it’s not easy to model or predict.
And with that, I found the answer: Although helpful and informative, good marketers don’t need to rely on sophisticated analytical tools to make decisions. Their experience, “gut,” and sometimes the hairs on their back of their neck do just fine.
by scott.gillum | Aug 13, 2012 | 2012, Observations
Big data is about to get bigger. Deliotte predicts that by the end of 2012 more than 90 percent of the Fortune 500 will likely have at least some Big Data initiatives under way. Companies will likely spend $1-1.5 billion to enable their organization to collect, analysis and use “big data” with the intent of gaining a better understanding their customers. But according to Doc Searls author of the new book Intention Economy: When Customers Take Charge that may be a waste of money.
Searls points out in a recent article in the Wall Street Journal, that as fast as companies are configuring systems to capture data at customer touchpoints, consumers are disabling collection sites. In May of this year, ClarityRay reported that the overall rate of ad blocking in the U.S. was 9.26%, and even higher on certain types of site and browser (download the report on ClarityRay’s website).
In May, Microsoft announced that the “Do Not Track” (DNT) feature will be turned on by default in the next version of Internet Explorer. Add this to Dish’s ad skipping product, Hopper and you have an increasingly less assessable consumer. What does this mean, well according to Searls it’s leading to a point where the supply side will yield influence, and ultimately power to the demand side, the consumer.
Searls book explores how customers will transact over the next 10 years, and the rise of Vendor Relationship Management (VRM), think CRM built for consumers to aggregate personal information and signal their intention to vendors on their preference, terms and desired price. As Searls points out, sites like Priceline and Travelocity, have started this movement but they are still “siloed.”
The tipping point for the next wave is fully empowered consumer, untethered by restrictive contracts, and siloed information. In this new world, consumers will have software that can integrate apps with the services offered by companies, saving time for consumers and creating commerce for companies in real time.
Imagine a business trip in which your phone apps for travel, budgeting, mapping, all work together to compare offers, make reservations, and filling out expense reports along the way.
What will it take to enable this revolution? Ultimately, it comes down to the recognition that a free customer is more valuable than captive one. Companies who will thrive will identify opportunities that take advantage of consumer’s freedom that they have, or want. A mindshift from thinking of consumers as “targets” that live in “populations” who need to be “acquired” or “locked in.” To an empowered individual buyer who will signal their intent to a company, as long as there is a trusted relationship.
In this personal empowerment revolution outlined by Searls, the future of buying lies not in investing in big data systems to figure out consumers, but rather by integrating apps that enable “small data” to be used by consumers.
Big changes for big data are looming on the horizon…
by scott.gillum | Aug 1, 2012 | 2010, Marketing
Original post date December 15, 2010
Last month I had the chance to be a panelist at a forum hosted by Wolfgang Jank and the Robert H. Smith School of Business at the University of Maryland. The topic was on Informatics – Data Driven Decision Making in Marketing.
Agreeing to participate without knowing what I would discuss, I searched my files reviewing old project work. Not only did I find a relevant effort, I also realized that I had spent two years working on building and implementing an insights program at a major Financial Services firm.
What’s interesting about the topic is that everyone will agree that they should be more data driven, or fact based, with their decision-making. Heads will nod when it’s discussed, it’s intuitive, and so the question…and the problem, is why doesn’t it happen?
The company I was working with had an abundance of data but were faced with two consistent problems related to the use of it:
- Reps wanted better insight
- Customers wanted a POV
The first issue we probably spent a good six months on defining what an ‘insight” was, how to create it, and who was responsible for doing it. The second issue was more complicated, and took much longer to resolve.
Over that two-year period, I learned how challenging it is for an organization to use one source of data effectively across the enterprise. Some of the challenges we uncovered were typical such as lack of resources, process, and funding. Others were more challenging: People funded their own resources and research to support their strategy, budget or group.
To begin to solve this complex problem we created a “data value chain” (see below). The starting point was having one centralized source for data. As we discovered, as data flows from across the organization to the customer, enhancements were needed to make it more valuable, like growth rings on a tree.
As data became more customized, and localized, it grew more valuable. This helped to identify why, for example, research that was being produced at corporate was not often used by the sales teams…it lacked relevancy, especially in regions outside of the US.
Once we got everyone on the same page the next challenge was to align the various groups in the organization across the value chain. We learned there could be as many as five different groups involved in handoffs as the data moved across the value chain. This help to explain why product groups were developing solutions without market insights, and regions were not leveraging corporate insights for business development.
Handoff points in an organization
As a result, we had to design process maps, hand-off points, engagement process, etc. The elephant in the room, and one of the biggest challenges was wrestling with the budget. The solution for that last huddle was turned out to be pretty simple.
The corporate “insights” team would work with those regions that wanted to work with corporate. Those regions had to be willing to fund resources to finish the “last mile”…building a solution or a customer business cases with a defined solution in mind. Even though everyone wanted more relevant insight, and more defined points of view, not all regions were willing to pay for it. Finally, to secure the funding to make the fixes we had to be able to answer a very simple question; “how does being more data driven provide value to the organization?”
The answer was getting the data closer to revenue or a sale….”turning data into dollars.” The epiphany wasn’t that the value was found at the end of the chain but the number of groups, and the coordination needed to be involved to reach that destination.
by scott.gillum | Jul 18, 2012 | 2009, Marketing
Original post date March 6, 2009
Tell me if you’ve seen this movie before. After spending months debating about the right type of segmentation to do, you finally agree, do the research and…it never gets used. Or how about this one, you get a request from sales for information you’ve already sent to them…multiple times.
It’s a horror movie and it gets play out every day in organizations all across the country. Why is it that we want “data” but then we don’t end up using it? Based on my experiences with clients, I believe it comes down to few common problems that are manageable, if known.
The top 5 problems I see:
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- Actionable Insight – as in the lack of it…it’s the #1 reason why data doesn’t get used. Far too often the Ph.D’s will put out data without having interpreting it for the intended audience which then sets up the next problem.
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- Language/Communication – call it taxonomy, communication style, whatever, data folks and everyone else (in particular, sales & marketing) speak different languages.
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- Overload & Timing – yes, analysis paralysis does exist but not the way you might think. If you’re in a data rich environment, you’ve probably experienced this. Just too much info flying around and as a result, it often gets ignored. It’s not that it causes people to not take action, as much as it is people taken action and ignoring the data. In other situations, especially involving marketers, it may be a matter of timing. They may be in too much of a hurry to get something out the door to wait on the data.
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- 60-70% Complete – critical pieces are sometimes missing so you can’t see the insight. The dots haven’t been connected. The person responsible for supplying the data doesn’t, and/or wouldn’t, see the connection.
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- Skill set – CMO’s when asked the top reasons (see the chart in the post below) for the need for new skills in their organizations mentioned; “greater segmentation of market” and “increase demands for analytics” in their top 5. The problem is that there aren’t many of them out there.
Why is this important now? Because everything you do or want to do, or are thinking about doing, will have to be backed by data in this economic environment…you’ll need a rock solid reason for getting, or spending a budget.
Five things to do about it:
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- Apply the “So What” rule – yes, this rule is typically used to help define a feature from a benefit but it’s also effective at drawing out insight from raw data. If the data guys are presenting information that you don’t “get” ask them “so what?”…as in, what is this data suppose to tell me? And keep asking until you get to the “so what.”
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- Help connect the Dots – if the story is missing help supply/coach on how or where to connect the other pieces. If you’re the user know what you’re looking for and provide guidance on where to find it. As I mention above, researchers may not know or wouldn’t understand the connection. This also applies to coaching on communication. Help them understand the language you speak.
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- Chunk it up – sometimes there is just too much to take in and process. Chunk information into more digestible pieces. Take some time and think about what various groups can digest and how often…especially if you’re in a data rich environment.
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- Provide plenty of lead time and direction – don’t expect to get something insightful and/or useful if you don’t give adequate notice or direction. Getting a report on market share won’t tell you how to increase it, or why you’re losing it. Combining trended quarterly market share, key consideration drivers, and sales coverage will…but it takes time to collect. Know what you’re looking for and how to get it.
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- Hire an expert – as was mentioned above there is more demand than supply of talented people who can pull insight out of data and drive action from the insight. If you have to, partner with a vendor. It should also help with the timing/speed issue mentioned earlier. Additionally, they will have tools/approaches that help force out insight.
Data…leads to Insight…leads to Action…leads to Data…the cycle of life. It’s time to turn this horror movie into an action thriller.
