It is, of course, a cliché to say that the marketing landscape is in the midst of rapid transformation. But the past couple of years have seen such dramatic and unpredictable changes that this is a fact worth repeating. From an exponential increase in digital channels in recent years, to increasing privacy regulations around the world, to the upheavals caused by the pandemic and recent geo-political tensions, companies and brands today must deal with complex challenges in marketing and marketing measurement. Technology-driven marketing analytics can help marketers navigate many of these challenges. Here are some major trends we can expect to see in marketing analytics in 2023 and beyond.

Privacy-friendly measurement techniques will see a resurgence
With the increase in digital’s share of advertising, techniques like Multi-Touch Attribution (MTA) have become very popular over the last few years for measuring digital marketing effectiveness using granular user-level data. However, the increased focus on privacy by regulators and consumers alike will bring in significant disruptions. Privacy regulations such as the General Data Protection Regulation (GDPR) and California Consumer Protection Act (CCPA), the gradual phasing out of cookies on the world’s most popular browsers, and signal loss due to Apple’s restrictions on IDFA on all iOS devices have altered the digital advertising landscape. Without the benefit of granular user-level data, techniques such as attribution will become significantly less accurate. Brands will increasingly explore other measurement techniques such as Marketing Mix Modeling that are privacy-friendly and rely only on aggregated data.

AI and ML will enable faster and smarter insights

 

If you have tried Chat GPT, you know that Artificial Intelligence (AI) and Machine Learning (ML) are no longer just hype. They will significantly transform how brands benefit from marketing analytics. AI will increasingly be used in various stages of the analytics process – quality control of data, building more robust marketing analytics models faster, and automating reporting and insight generation using Natural Language Processing (NLP) and Natural Language Generation (NLG). All this will translate into faster, smarter and more cost-efficient analytics and marketing insights for companies.

More companies will move marketing analytics in-house
With growing regulatory and competitive concerns, more and more brands are reluctant to share sales, customer and other sensitive data with marketing analytics providers. Outsourced analytics has also been time-intensive and prohibitively expensive, allowing companies run it only for their largest brands and markets. Companies that are investing in more computing power and even data science teams, will increasingly want to bring marketing analytics in-house to run analytics on demand, reduce costs and scale it to cover more of their marketing budget.

SaaS solutions will make analytics affordable for smaller companies

Marketing analytics was traditionally outsourced to large consulting firms or specialist analytics providers. The model was time consuming and xpensive, restricting affordability to only large companies with marketing budgets in at least in the tens of millions of dollars, if not more. Small and medium brands could not leverage the benefits of analytics to optimize their marketing plans.

Today, many advanced marketing analytics solutions are offered in Software as a Service (SaaS) models that require much lower investments, putting them within the reach of small and medium brands. These SaaS solutions are offered in full-service or in-house engagement models, are highly automated and intuitive, and are quick and easy to deploy and run on-demand. Affordable SaaS analytics solutions will also see wider adoption as more companies tighten their belts in expectation of a recessionary environment.

Analytic Edge provides a range of marketing analytics solutions that help companies and brands navigate today’s complex and dynamic business environment. Demand DriversTM is an end-to-end, always-on Marketing Mix Modeling SaaS platform that allows companies to determine the incremental impact of different marketing and non-marketing spends on revenue, profits and other Key Performance Indicators (KPIs). PriceSense enables accurate, data-based decision making on pricing. Analytic Edge’s Testing Tool allows brands to analyze the impact of planned marketing activities and take more informed decisions on implementation and roll-out. And our Dynamic Forecasting solution combines the latest data with AI-driven processes for highly accurate forecasts that factor in changing consumer behavior. Get in touch at [email protected] to learn more about how our advanced marketing analytics solutions can help your business grow.