With all the chatter about third-party cookies being finally phased out, the ad tech space seems to be in for a host of changes this year - from rethinking the marketing attribution models to ensuring data quality (in a cookieless world!) to the modifications that are yet to set in for programmatic advertising.

And to delve deeper into all this and more, exchange4media engaged in a chat with Priti Murthy, President, GroupM Nexus, who shared how marketers and advertisers should navigate these unknown waters.

Murthy spoke on data-driven strategies that help in navigating marketing attribution models, tackling data integrity challenges, harnessing the potential of Connected TV (CTV), and overcoming hurdles in the ever-evolving martech/adtech space.

Excerpts:

In navigating the evolution of marketing attribution models, the landscape has become multifaceted. How do you suggest marketers navigate this complexity while ensuring an accurate representation of consumer behaviour across various touchpoints?

It requires a strategic approach and a deep dive into the complexities involved. One such strategy is the adoption of a multi-channel attribution model that captures the various touch points across the customer journey is important. It could include the key things in the life cycle from first-touch, last-touch, linear or algorithmic attribution models. Deep dive into each stage and choose the one that aligns well with your business goals.  

You need to have a detailed understanding of the customer journey across various touchpoints that can help determine the key moments of influence and decision-making. Use the journey analytics to gain insights into the sequence and impact of touchpoints on consumer behaviour.

Leverage machine learning and artificial intelligence for analytics where you could use large data sets to identify consumer trends and marketing strategies. Additionally, AI-driven attribution models that can adapt and evolve based on changing consumer trends and marketing strategies can be implemented to gain key consumer insights.

Cross-device tracking to understand how consumers move between different devices during their buying journey is a great way to understand their behaviour.

Data integration and centralisation are also important. Once data is centralised, a unified data management system can ensure consumer behaviour is collated at one central source. It is a good idea to integrate data from online and offline sources to create a comprehensive view of consumer behaviour.

But there has also been an exponential growth in data volume, and with that maintaining data quality has become a significant concern. How can marketers ensure data integrity and relevance amidst this massive influx of information?

There are various ways to gain better control over data.

Start with establishing clear policies, standards, and responsibilities to ensure consistent data management practices. It is important to integrate automated validation checks into data pipelines to identify and correct errors in real time. If you haven’t done it yet, then establish a Master Data Management solution to maintain a single, authoritative source for critical data entities.

Deploy automation, a great automated data quality monitoring process with alerts for anomalies, enabling immediate corrective actions. Agility is a great way to manage data so, now is the time to embrace agile practices to adapt quickly to changing data requirements and business processes.

However, not everyone is adept at using data to organise training for users to instil a culture of data stewardship, responsibility, and awareness. Lastly, it is a good idea to invest in scalable and flexible infrastructure, including cloud-based solutions, to handle the growing volume of data effectively.

Along with the data boom, Connected TV also witnessed a pivotal year in 2023. However, there still seems to be ambiguity among marketers regarding its future trajectory. How can they capitalise on its potential more effectively?

The future looks very bright and Connected TV is expected to continue its growth trajectory in 2024. This is going to be fuelled by the increasing popularity of streaming services. So, as more viewers shift from traditional TV to on-demand content, marketers can anticipate continued ad spend on CTV platforms. Personalization, interactive ad formats, and data-driven targeting will likely be key trends shaping the future of CTV advertising.

One can also go a step ahead by deploying measurement and analytics to embrace advanced measurement tools to track and analyse the performance of CTV campaigns to refine strategies based on real-time insights.

Keep yourself abreast with emerging trends and devise strategic and data-driven approaches to leverage the potential of CTV in this dynamic and evolving media landscape.

Looking back at the trends that shaped programmatic advertising in 2023, such as AI-driven optimization and privacy concerns, what are your expectations for the upcoming year? How might the landscape evolve, and what trends should marketers prepare for in 2024?

In 2024, programmatic advertising is likely to see further advancements in AI-driven optimization for enhanced targeting and efficiency. User privacy-driven strategy, with an increased focus on ethical data practices, will be on the rise, something we are seeing with Google Chrome starting to deprecate third-party cookies in a phased manner.

Additionally, the evolution of contextual targeting and the integration of emerging technologies like blockchain may reshape the programmatic landscape. Integrated approach towards programmatic will be more important than ever and this means more money spent identifying and ensuring we are reaching the right users.

Old metrics & KPIs will see reduced relevance.

Any particular challenges that marketers and advertisers need to work on when it comes to the martech and ad tech space?

Integration and compliance are two major challenges in this space. So, I would think of investing in a unified martech platform to streamline integration and enhance data interoperability. Put in place robust compliance monitoring processes, adapting swiftly to changes in privacy laws.

Data governance plays a pivotal role, so ensure data quality, security and adherence to regulations. A good idea would be to prioritise technology development at the same time, ensuring compliance. In large organisations, communication also plays a pivotal role, so foster transparent communication with users about data usage, and build trust through clear privacy policies.  

The biggest challenge is aligning regulators, so proactively engage with regulatory bodies to stay informed and contribute to shaping privacy frameworks.