By Sandeep Pandey
Businesses are always keen to improve their return on investments in marketing spend. For achieving this objective, understanding the full cycle of the customer journey across various channels is necessary. In today’s digital era, customers are very discerning. They receive information about brands through various channels with digital ones dominating the scene. Apart from exposure to traditional advertisement through television, newspapers, magazine, and outdoor billboards; the world of influence has now moved to social media platforms like YouTube, Twitter, TikTok, Snapchat, Meta, and others.
The emergence of the creator economy has led to social influencers playing a big role in customers’ buying behaviour. According to Statista, the number of social media users worldwide is projected to reach a whopping 5.85 billion users by 2027 from an estimated 4.59 billion in 2022. Moreover, estimates suggest that around 2.5 hours is the time an average user spends on these platforms. Given several customer touchpoints, it becomes critical to understand the exact efficacy of each channel. Therefore, brands employ various models to gauge the impact.
Digital attribution and its changing trend
Digital attribution is the popular model followed by marketers to understand the impact of various marketing initiatives on sales. It is defined as the process of determining the effectiveness of different touchpoints in driving any performance or brand KPIs (key performance indicators) such as brand health, conversions, or sales. Under this model, marketing efforts track consumer behaviour across browsers, apps, and other digital interfaces. But privacy concerns are changing the landscape relating to digital attribution. Countries across the world are coming up with regulations to protect the privacy of users.
GDPR (General Data Protection Regulations) of Europe is a case in point. Similarly, Apple’s operating model iOS14 enables users to opt out of being tracked from apps and other sites. Google AdSense has also changed its attribution model. So, there is now a change in measurement due to the lack of support for third-party cookies along with a shift from precision-targeting of ads based on users’ internet behaviour. Cookie-based attribution has already started to rank lower in its accuracy for providing future forecasts.
These changes in the media and marketing world mean a new approach to data acquisition, access & measurement, which is more privacy-centric and complies with new regulations worldwide. Data scientists & mathematicians have started testing their new measurement solutions, which are more inclusive, strategic, and futuristic compared to earlier attribution solutions. Against this backdrop, econometrics models are becoming popular.
Econometrics model
With the fundamental aspect of digital attribution-cookie settings getting altered, econometrics models are being adopted rapidly. Econometrics is a statistical method used to analyse and measure the relationships between different economic variables, such as consumer behaviour and market conditions. In contrast to the digital attribution model, econometrics methodologies are often looked upon as historical measurement techniques, due to their dependence on past data sets to build relevant baselines, estimates, and benchmarking models. So, it is turning out to be a game changer due to its agility. As cookie-based attribution models slowly lose relevance, superior attribution models are being developed.
Many firms have developed innovative analytical solutions to overcome attribution concerns. Several new-age marketing analytics-focussed companies have deployed real-time ensembling techniques of various media & marketing models. Multiple models are built on a real-time data stream, which is powered by artificial intelligence and predictive analytics. With the aggregation of all the models, a business can have a holistic 360-degree view on a real-time basis of the various marketing efforts. A strong optimization engine, which is running at the backend, provides the most optimized mix to gauge the impact of any marketing campaign.
Also read: Twitter legacy users give Musk the cold shoulder as less than 5% accounts sign-up for paid blue tick
Interestingly, the accuracy of the new model is fairly high in measuring the impact of marketing effectiveness. Studies indicate that these advanced multi-domain designs, simulations, and state-of-the-art econometric & measurement constructs can predict future outcomes at more than 90 per cent accuracy. Moreover, the new model has been tested across categories and markets with equal ease and all the early indicators show that this is transforming the definition of digital measurement in a major way.
As the definition of privacy undergoes a massive change with nation-states taking proactive measures to maintain the privacy of individual citizens, marketing professionals have to leverage a new model powered through econometrics to gauge the marketing effectiveness of various channels. Marketing analytics and AI-powered algorithm will play a crucial role in defining the success of this model. Therefore, brands should collaborate with the right technology partner with execution expertise and experience to win the branding game.
(The author is CEO & Co founder, Skewb Analytics. Views expressed are personal and not necessarily that of financialexpress.com.)