Diffusion and democratization is a natural part of the life cycle of any technology, as cutting-edge technologies typically move from the laboratory, into the hands of a few early adopters, get commercialized by industry, and later become widely available to all. For example, the 1980s and ‘90s witnessed the arrival of accessible desktop computing, facilitated by easy-to-use Internet browsers. Computing technology thus moved from big server rooms in corporate headquarters/IT departments and onto the desktops of every single employee. That same computing power is now fully democratized and in everybody’s pocket.
Now in 2019, accessible, easy-to-use tools are transforming customer analytics, democratizing the field far beyond a few data scientists/experts and C-suite executives. Everyone (including data-savvy marketers) can increasingly and conveniently leverage data to inform better decision-making in real-time. According to Gartner, the number of “citizen data scientists” (non-experts who can conduct data analytics) will grow five times faster than the number of expert data scientists through 2020. Data democratization is coming, and you won’t need a Ph.D. to join the trend.
Drivers of democratization: Accessible customer analytics platforms
The widespread emergence of the citizen data scientist is being facilitated by more accessible, easy-to-use analytics capabilities. As happened in computing technology in the 1980s, user interfaces are getting friendlier (and more visually intuitive) while analytics platforms are using AI and machine learning to automatically perform a lot of the modelling (and writing of algorithms) functions that have previously been the preserve of trained data scientists.
Gartner describes this democratizing trend in customer analytics as “augmented analytics,” explaining that it “enables business users and citizen data scientists to automatically find, visualize, and narrate relevant findings without building models or writing algorithms.” Advances in artificial intelligence and AutoML, now integrated into customer analytics platforms, mean there’s less need for specialized data science skills to manage data. The era of the citizen data scientist, armed with accessible tools, is upon us.
Marketer as citizen data scientist
All this is extremely good news for marketing departments looking to leverage customer analytics to drive more personalized customer experiences (and revenues). There’s currently a big talent gap in the field of data/customer analytics, as companies compete for a scarce supply of qualified data scientists. As Gartner explains in its Top 10 Strategic Technology Trends for 2019, there just aren’t enough qualified data scientists currently available to meet the booming demand for data science know-how. Enter the citizen data scientist, supported by increasingly accessible analytics tools and platforms.
The democratization of customer analytics will enable marketers to deeply understand their customers in real-time, and deliver content to meet the dynamic needs of those same customers. Automated, accessible data science, in the form of customer analytics platforms that leverage AutoML, will allow marketers to access all the relevant data they need, in actionable form (i.e., as “business intelligence”), and without resource dependencies, will be able to quickly act upon it. Think of this capability as an always-on, 24/7 “lead nurturing engine,” one that plugs leaks in the marketing funnel and converts more leads into loyal customers.
The democratization of data science and the resulting emergence of the empowered citizen data scientist will enable many benefits, according to Gartner, including “the exploration of more hypotheses [marketers can quickly test their campaign ideas] and the identification of hidden patterns” in data. Marketers can track and respond to customer behaviors and make precise customer profiles as well as predictive analysis, allowing them to continuously drive ROI.
Citizen data science “enables users whose main job is outside the field of statistics and analysis to extract predictive and prescriptive insights from data,” notes Gartner. Empowered marketers can become citizen data scientists who remain proactive with customers instead of just reactive. These democratized analytics capabilities hold the promise of making the lives of marketers better and more data-driven.
Chuck Leddy is a Zylotech contributing writer.
If you liked this post, check out our recent blog post: Self-Learning in customer analytics: a primer.