Open data is critical for delivering contextual value to customers in digital ecosystems. For instance, The Weather Channel and OpenWeatherMap collect weather-related data points from millions of data sources, including the wingtips of aircraft. They could share these data points with car insurance companies. This would allow the insurers to expand their customer journey activities, such as alerting their customers in real time to warn them of an approaching hailstorm so that the car owners have a chance to move their cars to safety. Success requires making logical connections between isolated data fields to generate meaningful business intelligence.
But also trust is critical to deliver value in digital ecosystems. One of the key questions for big data is who owns the data. Is it the division that collects the data, the business as a whole, or the customer whose data is collected? Forrester believes that for data analytics to unfold its true potential and gain end user acceptance, the users themselves must remain the ultimate owner of their own data.
The development of control mechanisms that allow end users to control their data is a major task for CIOs. One possible approach could be dashboard portals that allow end users to specify which businesses can use which data sets and for what purpose. Private.me is trying to develop such a mechanism. It provides servers to which individual's information is distributed to be run by non-profit organizations. Data anonymization is another approach that many businesses are working on, despite the fact that there are limits to data anonymization as a means to ensure true privacy.
Mobile World Congress (MWC) is “the” event in mobile. It is the event where Samsung, HTC, Huawei, Sony, Microsoft, LG … well, really everyone (but Apple) will launch new mobile phones, tablets, and wearables. And, yes big-screened mobile phones are still “in.” I’m more likely to buy a leather jacket with bigger pockets or a larger purse than to buy a smaller phone.
Thousands flock to Barcelona annually to hold these devices in their hands. Words too often fall short in describing the feeling of holding the next Samsung device in your hand or the emotions of delight and bewilderment when you turn the device on.
The question then is: “So what? What does it mean for my company?”
A version of this post originally appeared on AdAge.
It's harder than ever to earn your customers' loyalty. They are "always on," have instant access to myriad choices, and can easily find the cheapest prices from any supplier. Many companies think they've solved this with a loyalty program, but the competition is stiff there, too. On average, consumers belong to eight loyalty programs -- the majority of which are ruled by points, discounts and financial rewards. And let's face it: These transactional benefits are more about increasing frequency and spend than influencing emotional loyalty and devotion to a company.
The bad news? Traditional approaches to loyalty don't cut it anymore.
The good news? I'm not going to tell you to scrap your loyalty program. But, in my new report on customer loyalty, I am going to tell you to reframe how you think about your program. It should be treated as one of several tools -- alongside customer experience, brand and customer service -- that helps foster customer loyalty wherever customers interact.
Be A Loyalty Company, Not Just A Company With A Loyalty Program
Truly great loyalty strategies create a meaningful exchange of value between the company and the customer. This exchange encourages customers to share all kinds of profile, preference and behavioral data. And the insights derived from that customer knowledge have broad applications for all customer-facing strategies, and should radiate out across the enterprise to do the following:
Just a few years ago, when big data was associated primarily with Hadoop, it was like a precocious child…fun for adults, but nobody took it seriously. I’m attending Strata in San Jose this February, and I can see things have changed. Attendance doubled from last year and many of the attendees are the business casual managers – not the blue jeaned developers and admins of days gone by. Big data is maturing and nobody takes it lightly anymore.
Industry analysts travel—a lot. It is, therefore, no surprise that I care deeply about airlines’ frequent flyer programs and track the changes to those programs as closely as baseball obsessives track star players’ slugging percentages. When I want information on what these changes mean practically in my situation (Will the new loyalty program make it harder for a 75k+ elite member looking to book a companion ticket’s upgrade on an alliance partner airline, for example), I typically do not turn directly to the airline. Instead, I log on to Flyertalk, a forum that bills itself as “the largest expert travel community.” The forum—populated by thousands of frequent fliers far more obsessive than I will ever be—consistently houses discussions of exactly the thing I want to know.
The lion’s share of people answering questions on Flyertalk and other forums like it—Cruisecritic for the cruising fans, TripAdvisor for travel and hospitality broadly, AutomotiveForums for car enthusiasts, etc.—are other consumers, albeit well-informed ones. But these non-brand controlled communities provide opportunities to brands to differentiate themselves through service. Because affinity communities have barriers to entry, including registrations and jargon, community members are usually deeply interested in the topic at hand. In communities that regularly discuss brands, these customers are also more likely to be exactly the type of high-value customers that companies want to provide with great customer experiences. But brands need to decide when and how to engage customers in these forums they do not control.
It’s not news that business user self-service for access to information and analytics is hot. What might not be as obvious is the overhaul of information-related roles that is happening now as a result. What’s driving this? The hunger for data (big, fast, and otherwise) to feed insights, very popular data visualization tools, and new but rapidly spreading technology that puts sophisticated data exploration and manipulation tools in the hands of business users.
One impact is that classic tech management functions such as data modeling and data integration are moving into business-side roles. I can’t help but be reminded of Bill Murray’s apocalyptic vision from “Ghostbusters:” “Dogs and cats, living together… mass hysteria!” Is this the end of rational, orderly data management as we know it? Haven’t central tech management organizations always seen business-side tech decision-making (and purchasing, and implementation) as “rogue” behavior that needed to be governed out of existence? If organizations have trouble now keeping data for analytics at the right level of quality in data warehouses, won’t all this introduction of new data sources and data lakes and whatnot just make things worse?
Well, my answers are “no,” “yes,” and “no” in that order. The big changes that are afoot are not the end of order and even though “business empowerment” translates to “rogue IT” in some circles, data lakes/hubs and the infusion of 3rd party data have actually been delivering on their promise of faster, better business insights for the organizations doing it right.
What’s taken artificial intelligence (AI) so long? We invented AI capabilities like first-order logical reasoning, natural-language processing, speech/voice/vision recognition, neural networks, machine-learning algorithms, and expert systems more than 30 years ago, but aside from a few marginal applications in business systems, AI hasn’t made much of a difference. The business doesn’t understand how or why it could make a difference; it thinks we can program anything, which is almost true. But there’s one thing we fail at programming: our own brain — we simply don’t know how it works.
What’s changed now? While some AI research still tries to simulate our brain or certain regions of it — and is frankly unlikely to deliver concrete results anytime soon — most of it now leverages a less human, but more effective, approach revolving around machine learning and smart integration with other AI capabilities.
What is machine learning? Simply put, sophisticated software algorithms that learn to do something on their own by repeated training using big data. In fact, big data is what’s making the difference in machine learning, along with great improvements in many of the above AI disciplines (see the AI market overview that I coauthored with Mike Gualtieri and Michele Goetz on why AI is better and consumable today). As a result, AI is undergoing a renaissance, developing new “cognitive” capabilities to help in our daily lives.
It's February: time for another S&R Analyst Spotlight Podcast! This month, Forrester VP, principal analyst, and Zero-Trust creator, John Kindervag, joins us. Listen in to learn more about John and his research. While you're at it, be sure to check out our First Look newsletter, which contains an interview with John along with links to his most recent and upcoming research. If you are not already signed up for our First Look newsletters, please email email@example.com.
Today marks the beginning of the Chinese New Year. Kicking off the 2015 lunar calendar and the year of the goat (or sheep or ram), today celebrates the emergence of spring, the coming together of families, and the arrival of good fortune. Given China’s prosperous technology evolution, the superpower has a lot to look forward to. According to Forrester’s Consumer Technographics® data, the country is already home to the most mobile-savvy population on the planet, with nine out of every 10 metropolitan Chinese online adults using a smartphone; within the next two years, the nation will see an additional 200 million unique smartphone subscribers:
What will happen when the world’s largest mobile phone market becomes even bigger?
Any procurement or asset management professionals who have seen the new movie based on E.L.James’ best selling novels may have noticed the similarity between the eponymous antihero and a license management services consultant. Mr. Grey will use charm and threats to persuade you to run his audit scripts on your network. You have an obligation to demonstrate your compliance with the software license terms, but that doesn't mean that you have accept his opinion about what those terms actually mean.
Sources inside some large software companies tell me that license audits generate 20% to 30% of their license revenue. Although a lot of that will represent deliberate or reckless under-licensing, many of the disputes that I hear about involve software salespeople abusing some licensing shades of grey to pressurize customers into paying them money. It is difficult to predict how a court will interpret nineties contract language in the current technology context, so many companies pay up rather than risk a compliance lawsuit. Here are five questions of interpretation that no lawyer can answer:
Who is really using my software? I continue to hear risible interpretations of ‘use’ and ‘access’, such as the software company that claimed motorists were users because they saw output from its database when they drove past an electronic road sign. I’ve previously suggested a standard interpretation of use in my report Let's Clear Up The "Indirect Access" Mess based on the concept of interaction - i.e. both input by a user and output by the software. Enterprises need to persuade their vendors to accept this interpretation urgently, otherwise the Internet Of Things will bankrupt you.