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  • Advertising

5 Data Driven Marketing Trends for 2019

Team InMobi
Team InMobi
5 min read
Posted on January 07, 2019
5 Data Driven Marketing Trends for 2019

In 2019, what will be the biggest data driven marketing trends? What data-led marketing strategies will take the lead in the new year?

To find out, we gaze into the crystal ball to reveal how data-focused marketing execution will evolve in 2019. Here are our top five predicted trends for the new year.

Interested in learning more about the biggest trends in ad tech and martech in 2019? Be sure to download our 2019 trends report today to see what we think will be huge in the new year.


1) Greater Emphasis on Artificial Intelligence and Machine Learning

In this day and age, it’s hardly surprising to say that artificial intelligence (AI) is a key trend. After all, it seems as though everyone is talking about AI and machine learning (ML).

But beyond the buzzwords, what does this actually mean for marketers? How can marketers and advertisers actually benefit from AI and ML? Likely, expect the following applications to come further to the fore in 2019:

  • Predictive analytics - Through the analysis of previous behavior and action, ML algorithms can help predict the future. This is hugely beneficial for marketers, and these kinds of applications will become even more popular in 2019. Predictive analytics can give marketers accurate insights into how their campaigns and efforts are likely to perform, helping them for effectively allocate their time and limited budgets.
  • Prescriptive analytics - This takes predictive analytics one step further. Instead of just predicting likely future actions and behavior, prescriptive analytics offers concrete guidance on what steps marketers should take to see specifically desired actions going forward. For example, prescriptive analytics algorithms can help marketers and advertisers analyze their planned ad creatives to see both how they would like perform in the real world and offer guidance on what changes should be made to the creatives so that they perform even better.
  • Lookalike modeling - As lead generation and demand gen become ever more critical to marketers, it behooves them to spend their time only going after prospects that are actually likely to convert into a sale. This is the same reason why account-based marketing is taking off right now. Lookalike modeling can help marketers achieve these kinds of goals. These algorithms look at the common characteristics of existing customers and then provide input on who isn’t a client but would likely be one since they share many characteristics with existing consumers.
  • Fraud prevention - As ad fraud grows in reach and sophistication, marketers continue to struggle against it; it continues to eat up budgets and cause frustration. But, this is a problem rife for disruption thanks to AI. ML algorithms can help to detect anomalies before problems ever arise. Essentially, these algorithms can predict where issues could arise before they ever become a real-life problem.

“We see the limitless potential for machine learning in digital advertising. Current advancements are blurring the lines between human and machine as evident in applications like sentiment analysis – machines are increasingly able to identify and categorize the opinions expressed in a piece of text, in order to determine whether the writer’s attitude towards a particular topic or product is positive, negative, or neutral. Nuance here is always evolving as language expands and includes things like sarcasm and emoticons to express meaning. Rapid advances in deep learning are allowing computers to process images and video in a more human-like way. These advancements will enable a more robust generation of brand safety and fraud solutions that will help to protect digital advertising investments.”
Harmon Lyons, Senior Vice President of Global Business Development at IAS.

2) Greater Focus on Data Quality, Not Just Amount of Data

Remember when “big data” was the biggest buzzword in data driven marketing? It used to be that volume, velocity and variety were the key variables in big data, whether related to user data, customer data or any other type of data.

But what about veracity? What’s the point of having a lot of data if it’s not accurate or verifiable?

Getting a lot of data to analyze is the easy part. The hard part is determining how much of it is good and, therefore, actually useful.

This shift from quantity to quality is already underway, but this transition will take on new urgency in 2019. In the new year, expect organizations to focus far less on the amount of data they have and more on its inherent and intrinsic value to the marketing department specifically and the organization as a whole.

3) Greater Focus on Consumer Engagement and User Experiences, Not Just Conversion Rate

In data driven marketing, historically customer insights was equated with hard metrics like conversion rate, ad views, clicks, etc. But, by focusing on just these kinds of single actions, marketers are missing the bigger picture.

What does the entire customer experience look like? After all, it’s rare that seeing one ad will lead to a sale. How do other inputs over time impact a prospect’s likelihood of becoming a paying customer? And, what goes into keeping that paying customer around for a long time and not churning?

In 2019, savvy marketers will use data to more effectively quantify all components of the user experience.

4) Development of Holistic, 360-Degree Customer Profiles

For many brands, knowledge on the customer is coming from distinct endpoints like mobile device IDs. But humans are more than just a number. In the new year, marketers will be smarter about how they look at and aggregate customer data, in order to develop more holistic, all-encompassing profiles of who precisely each prospect/customer is and what really makes them tick.

“From a data perspective, probably the most important change we can see is the collective effort towards greater data integration. We have all this data with us – transactions, channel engagement, support inquiries, etc. - but, ultimately, it’s information about the same consumer. What we want to be able to do is get a 360-degree customer view – who they are, what they like, how they engage with us, etc. – all at one place, and then use this data to communicate with them in a more personalized and relevant way. Stitching together data becomes important not only across functions, but across channels as well – both offline and online.”
Rana Saha, Senior Director of Growth Marketing at Grab

5) Digital Marketing is Increasingly App and Programmatic Driven

The media landscape of 2019 is more fragmented than ever before. For marketers, their target audiences may see ads on billboards, on TV, in apps, in magazines and in newspapers, just to name a few examples.

However, in 2019, apps will be the main channel marketers use to reach their target markets. As mobile devices and their apps become more popular than ever before, marketers will need to reach their core audiences where they are.

This push to apps extends now to television sets too. As over-the-top and connected TV rise in popularity, marketers will further focus on these channels in 2019 and beyond. And, just like with mobile devices, these TV sets and video platforms are all powered by apps.

In-app advertising and marketing provides a veritable treasure trove of data, in large part because of how central programmatic media buying is to this environment. According to our latest Mobile Programmatic Advertising Trends report, 56 percent of all mobile in-app ad spending conducted through the InMobi Exchange was spent programmatically.


What do you think will be the biggest data drive advertising trends of 2019? Let us know on social media! Send us your comments and feedback on Twitter or LinkedIn.

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