Streamlining Digital Media Measurement in the Age of AI

Are advertisers ready to face the challenges of navigating valuable metrics from the abundance of real-time data? If yes, which KPIs align with their business objectives, and how are AI-powered insights helping them?

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  • Leveraging AI to augment modern-day digital solutions can allow brands to cut through their data clutter and build a solid measurement stack that aligns with their business objectives.

    In today’s fast-paced digital landscape, the shift towards digital media has been revolutionary. It is, therefore, seen that digital media spending has witnessed an increase with advanced technologies and changing consumer behaviours, leaving traditional media behind by huge margins. 

    The reports of IPG Mediabrands highlight that the Indian advertising market will continue to show staggering growth of 11.4%. By 2030, a striking 75% of total spending will likely be allocated to digital channels, as per a report by management consultancy Redseer. It underpins what advertisers require: trimming their measurement strategies to find effective ways through this digital frontier.

    However, using a streamlined measurement stack in the digital space, advertisers are exposed to a series of metrics that go from ad impressions to figuring customers’ cost per acquisition and lifetime value. In such an avalanche of metrics and the influx of real-time data, capturing the exact key performance indicators (KPIs) that impact brands can be daunting.

    The campaign business objectives need to be aligned to identify the suitable KPI. The advertiser must ensure that tagging and tracking are done correctly with the use of appropriate tracking tools like Google Tag Manager and Tealium, among others, to ensure there is no disruption of data flow from analytics to ad solutions. 

    Once data accuracy is ensured, metrics must align with the brand’s objectives. Let me give you an example: the cost per acquisition would be one of the very important KPIs in a set of secondary metrics like funnel dropouts, conversions, cost per click, and click-through rates for a young brand trying to acquire users.

    For a brand that wants to enhance its appeal, metrics like brand lift in awareness and consideration become important. These could be digital solutions like Ads Data Hub and Meta Advanced Analytics.

    Another example is the key metrics retained should complement those of acquisition. For example, a big brand that focuses on customer retention might be interested in repeat purchase rate and customer lifetime value among its metrics. All these metrics provide insight into the effectiveness of retention efforts and the overall value derived from existing customer relationships. This makes the measurement of digital media even more complicated, considering that the KPIs are conflicting due to a mismatch between the tactical and strategic objectives.

    For example, a young brand may find itself in a catch-22 with a high cost per acquisition and low return on ad spend (ROAS). While these might be discouraging metrics from the point of view of performance in the short term, investments into advanced modelling techniques deriving KPIs, like the lifetime value of acquired users, might offer, in turn, a form of justification by shedding light on the long-term value that is brought into the business. In most instances within branding campaigns, advertisers base their strategy only on traditional metrics such as reach, view-through rates (VTR), click-through rates (CTR), and so on.

    The accurate measure of success, however, will be tracking KPIs that indicate an increase in brand awareness or consideration lift, which will be measurable with the use of digital survey methods, like Ads Data Hub. Advertisers, therefore, need to take a holistic approach that considers the KPIs that matter toward long-term goals, not just short-term gains. This will open a window for the advertiser to close the gap between the tactical and strategic objectives, enabling the latter to gain much insight into the digital media effort while driving decisions that will benefit their businesses from sustainable growth.

    As time goes by, artificial intelligence (AI) is emerging as the greater technology that takes a core function in measuring and optimising digital media. Among the most recent advanced developments for advertisers are AI-powered Business Intelligence (BI) chatbots, which can generate real-time insights and answer your business questions.

    Also Read: Why Brands Must Back Up Their Digital Efforts 

    What is more, enabled by insights and optimisation powered by AI, advertisers will revolutionise the industry by making data-driven decisions at an unmatched speed and level of accuracy. We at PivotRoots envision and realise the transformational potential of AI in digital media measurement. Therefore, we strive ahead to be the frontrunners in developing AI-driven BI applications that leverage advanced approaches, including Language Model-based algorithms, and serve actionable insights in realizing efforts towards optimisation.

    In other words, with digital media increasingly capturing a larger slice of the advertisement space, streamlining measurement strategies has never been more imperative.

    Therefore, if the latest tools are smartly aligned with KPIs and business objectives through advanced analytics and AI-driven solutions, advertisers can very well unlock digital media’s full potential to derive meaningful results for their brands in the AI era.


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