Marketing goods and services is becoming increasingly complex, and to gain a competitive advantage machine learning and data analytics are required to foster insights. A new tool for this comes from conDati.
conDati Marketing Analytics is a cloud-based service that applies data integration, data science and machine learning to help marketers understand and improve the performance of digital campaigns.
conDati is designed for continuous campaign performance monitoring, reporting and analytics. To understand more about marketing in the digital world and about the new platform, Digital Journal spoke with conDati’s CEO Ken Gardner.
Digital Journal: How important is data for modern businesses?
Ken Gardner: As they say in the context of Industry 4.0, “data is the new oil.” Some of the most obvious examples of the impact of Big Data are the huge businesses that simply wouldn’t exist without cost-effective and rapid access to Big Data, with Facebook, Uber, Airbnb, and Netflix only being some of most prominent examples.
Another segment is represented by the new businesses built on data collected by and/or generated within the physical product. Tesla, smart homes, smart appliances, robotics, and the new generation of airplane engines are easy examples.
The third segment is data used for operations within companies and other organizations. Access to customer data, market data, and production data, is what allows companies to simultaneously solve for growth and agility, which traditionally have come at the expense of each other. The wave of “digital transformation” initiatives sweeping enterprise-class companies is one expression of this: the legacy systems in big companies were designed to create high-performance data silos for specialists. Growth imperatives now demand faster response to new information. Transparency, access and speed of information exchange are now critical to competitive advantage and commercial success.
DJ: How did you develop the conDati Marketing Analytics?
Gardner: conDati Marketing Analytics was developed to give marketers complete visibility into the financial performance of their digital marketing activities and thus provide the ability to improve them at the points of greatest impact, resulting in clear, measurable and definable improvements in the ROI on marketing.
Like martech itself, the conDati service is affordable because of the economics of cloud computing. The algorithms behind conDati’s data science aren’t new, but to provide this service 10 years ago would have cost hundreds of thousands of dollars per month. With advances in both technology (storage, servers and communications) and business models (e.g., per-second pricing from AWS), conDati’s service can now be provided for only thousands of dollars per month.
conDati combines cloud economics with years of expertise in the management of big data with world-class data science to deliver a unique capability to marketing leaders and hands-on marketers.
DJ: What functionality does the conDati Marketing Analytics provide?
Gardner: conDati solves the foundational problem of marketing reporting by delivering automated, continuous, complete, correct, and integrated reporting and analytics on the financial performance of digital campaigns. With conDati, marketers use 100 percent of their data instead of 1 percent, with current results rather than days-old results; without manually-introduced errors; having eliminated all the work time currently required to create reports; and with all the important information included in a way that a CMO can get a full vision of past, current and future campaign performance in a few minutes per day (instead of hours for a partial view). And there’s no wait time: one of the reasons for the swift adoption of the cloud is that you can be up and running with your data in a week, rather than waiting a year or two for IT to deliver a major project.
In the current model of spreadsheets and/or silos, another problem is data navigation. How does a marketer know what to look at/look for or how to find it? conDati’s service is navigated with a user experience inspired by the best of consumer interfaces; finding your critical marketing performance data in conDati is as easy as finding your favorite movie. And if you want further detail on a campaign, source, channel, or medium, drilling down to the most granular level of detail is fast and intuitive.
Once all the data is in a single unified and accessible data asset, we can use machine learning data science for both predictive and prescriptive analytics, based on each customer’s own data.
DJ: How important is automation to the process?
Gardner: One of today’s core problems is the work time required for all the manual reporting. Anecdotally, some marketers spend up to 90 percent of their work hours assembling data and reporting and only 10 percent on analytics and marketing. conDati’s automation eliminates those manual hours and reduces the time needed to understand the analytics from hours to minutes, thereby freeing these highly paid, highly trained professionals from rote tasks and giving them the time and the insights to do what they’re paid to do.
Secondly, the predictive and prescriptive analytics are possible only because of the ability to apply high computational power at low price points. Without automation, forecasting and anomaly detection wouldn’t be possible inside any useful timeframe.
DJ: Which types of metrics or analytics are important for business? Is data relating to social media important?
Gardner: The most important metrics for business are the outcomes. How much revenue did the company generate, at what cost? Those numbers define market success, shareholder value, and the future nature — or even existence – of a company. Every other metric that can be tracked is tracked in an effort to predict and/or influence what the revenue and cost outcomes are going to be. Many of those — including different types of social media data, depending on the industry and the company — are useful and valuable, but they are primarily measures of activity, which does *not* necessarily translate directly to revenue and cost outcomes.
DJ: Which types of companies are using the technology?
Gardner: conDati has early customers in four industries: E-commerce, both B2B and B2C (recognizing that e-commerce today is mostly B2C); Higher education: colleges and universities, focused on applicant acquisition; B2B technology companies (distinguished from e-commerce because their revenue transaction is not conducted over their websites); and digital media, focused on audience acquisition
DJ: What other projects are you working on?
Gardner: conDati’s current focus is to scale our customer base following our commercial launch in May. There are a variety of questions and problems in performance marketing that can be addressed by different machine learning algorithms, and we are working with our early customers to understand those problems in order to prioritize them and solve the most important.
To understand more about the growth and application of digital marketing, read out follow-up article “Advances in digital marketing analytics: Interview.”
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