ice skater alone on ice, practicing figure 8
PHOTO: VanveenJF

Marketing has been experiencing rapid change, and with it, we've seen the evolution of the analytics space. Marketers must evaluate how well their strategies adapt to these changes and should expect every competitor to have measurement and analysis at the forefront of strategic plans in 2020. 

The way to stay ahead of the competition lies in forecasting from the data collected. Marketers should see analytics tactics and features that make that white space easier to experiment with in the years ahead. Here are a few ideas.

The Rise of CXO: Customer Experience Optimization

Customer experience is a proven driver of establishing long-lasting connections with your intended customer base. Gartner predicts two-thirds of customer interactions will be IT-enabled, up from 50% in 2017. The opportunity for marketers here lies in adjusting budget and resources to focus on those channels found to have the greatest influence on customer experience. Expect variations of predictive analytics and evaluations to unlock the right combination of elements that sustain a good customer experience. The practice of refining these elements to improve customer experience is customer experience optimization (CXO).

Better Planning of Inferential Statistics Against Business Metrics

Programmatic campaigns, like customer experience, are everywhere, an essential element in engaging customers at the right time. But to understand if programmatic campaigns are yielding results, we need to measure associations — of product purchases or behavior that leads to a sale — through inferential statistics such as Bayesian models. Not every statistics metrics easily relates to a KPIs. So marketers must consider how metrics best relate to an advanced analytics model and the statistical measures it produces to better understand the business impact.

Related Article: How to Improve Data Literacy Among the Non-Quants in Your Organization

New Ideas for Immersive Advertising Emerges

Immersive experiences provided through virtual reality (VR) and augmented reality (AR) technologies will encourage a rethink of how marketers use tags. Tags were created to link a click ad — and later, social media ads — to a website or landing page. With more brands creating richer virtual experiences, or discovering ways to overlay content on real-world visuals, better tagging technology will likely emerge to make measuring engagement in these new worlds possible. A few open source developer kits like ARToolKit have been available for years to leverage virtual reality media, but increased marketer interest in dynamic immersive content should encourage more innovative applications to emerge.

Analytics Get Granular and Proactive

Analytics will head back to the future. Analytics solutions were originally conceived to monitor diagnostics issues with websites — that's how Google Analytics got started. But with the wider range of formats and channels for digital media available today, marketers need better diagnostics. Data generated from websites and apps is being used in advanced models that require statistical rigor — meaning no missing values and enough data to determine its use in a predictive model. Marketers now need analytics which can evaluate channels to alert them when data is missing. The capability has been available for a while, but expect to see more data exploration features introduced and/or current platforms adjust their features to provide more nuanced alerts.

Related Article: Decisioning – The Only Way to Accelerate Analytics to Value

Better Data Quality Management Is on the Horizon

Data quality management will also be a big driver in 2020. Marketers are no long satisfied with trusting a platform entirely for the quality of metrics — just look at the criticism Facebook faced for its video ad metrics as an example. Moreover, a wider scope of data type structures used for programmatic advertising requires methodologies to ensure that errors are not systematic, so developer-influenced methods like DataOps will be essential to maintaining data quality and preventing compliance mishaps.

New Advertising Platforms Will Extend Analytic Opportunities (and Challenges)

As digital devices, such as home voice speakers, proliferate, marketers have yet another avenue to connect with customers. But the breakout platforms in 2020 will be associated with podcasts and streaming networks (Netflix, Disney Plus, etc.). Amazon’s successful bid in advertising — it now has the third largest share of digital advertising spend behind Facebook and Google — shows how a platform with a sizeable audience can offer an alternative to social media and online search.  

Expect the platforms hosting podcasts and streamed broadcasts to expand their own advertising options — offering yet another analytic channel to manage.

Related Article: Is it Time for Marketers to Invest in Amazon Ads?

The Billboards Strike Back

Another analytics opportunity may be just outside your window. Digital billboards are a great starting point for engagement and marketers should expect the trend to continue. Billboard inventory along high foot or vehicle traffic is becoming more digital, allowing for more messages that can complement other display media like OTT. Marketing managers who are still unsure how to attract consumer attention may want to test tried-and-true platforms like billboards to drive customer interest.   

Related Article: How Digital OOH Ads Take Your Message to the Streets

Open Source Opens the Range of Data Visualization Choices

Marketers have more choices for visualization applications than ever before. Supporting libraries and panda programs for open source languages like R programming and Python, respectively, have allowed visualization techniques that have been around for decades to gain wide-scale application. The R programming library gglot2 is an example. It applied principles from grammar of graphics, a layered framework, within the environment for R, which arranges data as matrixes for statistical calculation. The end result is a new ability to display treemaps, arc diagrams and other visualizations that can better relate the story behind the data.