Half of enterprise marketers surveyed by Gartner who have deployed a CDP say its their CRM system…” While Gartner argues there is “redundancy” with “other, more mature marketing technologies,” limiting CDPs to a Marketing and Advertising discussion skates over the technology as heir apparent to the promise of big data. While each of these technologies takes up the task left behind by big data, Customer Data Platforms represent the most “transformational” of the hyped-up tech.Īs Gartner notes in their Hype Cycle report, “Marketer’s expectations for CDPs remain at an all-time high, but the reported use of the technology differs from the advertised capabilities. The ability to (re)instill trust between the customer and the company.īig data set the table for these principles, and now we’re reaching the moment for them to be served up to marketers, IT professionals, and customer experience teams as achievable goals. The ability to act intelligently based on everything you know about a customer. The ability to collect and control your customer data. However, in the intervening decades between the heyday of big data and today’s world, new guiding principles have emerged beyond simply velocity, volume, and veracity. The hype may be the same- turning all of the data we collect into valuable, meaningful information. In their own ways, each one of these take a segment of the original promise of big data and turn it into a fully-realized part of the martech stack. The four technologies Gartner called out as transformative in their most recent Hype Cycle all circle around one common theme: making data useful. For this reason, even in 2019, analytics, AI and big data projects have an astonishing 85% failure rate. Then they ran into a slew of challenges, all stemming from the original sin- er, promise - of big data: the expectation of meaningful insights from all that information.Īs companies discovered, there was a lot of work involved and the insights often came too late in a world beholden to meet real-time needs. Now that companies were trained to think big about data, they had tons and tons of data sitting in on-site or cloud-based servers. Further evolutions like Cassandra refined the rough edges to increase the velocity to achieve insights from the data. When Hadoop came to the market, it promised a way to cheaply store and retrieve tons of unstructured data, organizing it for simple retrieval to run analytics. What Do You Do With a Problem Like Big Data? When put into that context, Gartner’s “Hype Cycle for Digital Marketing and Advertising 2019,” in which they’ve identified four technologies that will “transform how marketers run their technology ecosystems,” tells a fascinating tale of where the promise of Big Data was unable to be fulfilled during the zenith of its own atmospheric rise. But the challenges of realizing that promise of big data remains. Regardless of industry, data plays a critical role in every business’ strategic goals and, when not taken seriously enough, represents a source of immense risk (just ask a company like British Airways, which was fined $230 million for violating the GDPR). Here we are, five years on from that assessment, and the promise of big data has become an indelible part of the enterprise information landscape. As InfoWorld wrote in a 2014 reflection on the decline of big data, “When what is now commonly called ‘big data’ becomes no more special than other data, when the technologies used to store and process this data become commonplace, then will the hype around big data start decline, and fall from grace.” Though the hype for big data has been put out to pasture for years now, the central tenets of big data remain with us: volume of data, variety of sources, and velocity. While the hype has died down on big data, companies are still dealing with its effects- arguably, the hottest technologies of today are in response to the complications introduced by the big data mentality of collect everything. Over a decade after “Big Data” became the next big thing, the imperative to collect every piece of information- whether structured or unstructured- remains ingrained in the fabric of enterprise businesses. When Gartner released their “ Hype Cycle for Digital Marketing and Advertising 2019 ,” I couldn’t help but think to myself, This is the world left in the wake of big data.
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