Advent Of Explainable AI, ChatGPT Make Marketing Analytics More Engrossing

Rising cost pressure and ever-increasing competition are prompting companies across sectors to adopt an advanced version of marketing analytics- ‘explainable AI’ for ensuring a better return on their investments.

Explainable AI is a set of tools and frameworks to help the user understand and interpret predictions made by machine learning models. Essentially, organisations are able to understand the reason behind certain forecasts thrown by the algorithm model than just imitating it without reason. Such understanding removes the mystery behind AI modelling and democratises the usage of analytics across sectors. Moreover, deeper insights into the prediction model enable companies to know the exact outcome of any marketing investment and plan judiciously for better results. According to projections, the global ‘explainable AI’ (XAI) market size is estimated to touch USD 21 billion by 2030 from USD 3.5 billion in 2020. 

Not only explainable AI but also generative AI tools like ChatGPT are likely to change the way marketing initiatives are getting leveraged. Given its ability to understand natural language queries, the ChatGPT kind of tool is going to disrupt search marketing in a big way.

Hearteningly, many new-age companies are leveraging the power of explainable AI and ChatGPT by integrating those into their marketing analytics solutions. Skewb Analytics is one such new-age data analytics firm. Evolved during the pandemic by industry veterans Sandeep Pandey, Snigdha Gupta, & Shubham Chhajed, the company currently helps organisations to realise the full potential of marketing analytics powered through cutting-edge AI applications.  

Commenting on these relatively new domains of AI, Cofounder & CEO of Skewb Analytics, Sandeep Pandey, said, “Explainable AI holds the future of marketing analytics. This is already democratising analytics usage and enabling enterprises to get deeper into what investment options would drive growth immediately and in the long run. Management is also able to drive sales growth leveraging explainable AI.” ChatGPT, like generative AI tools, is something to watch out for in the near future, he added. 

Customised offerings:
The demand for marketing analytics is on the rise to measure real-time RoIs (Return on Investments) apart from saving costs. Leveraging marketing analytics tools, organisations are increasingly identifying inefficiencies, tapping new revenue opportunities apart from understanding the customers' needs better. Especially personalisation at scale can only be achieved through advanced marketing analytics tools. By accessing customers’ interest and behaviour data sets, businesses can build customised marketing campaigns. For instance, an apparel company can design a better campaign targeting youngsters 15-20 years of age by knowing their preferences. Such a campaign will be very different for customers in the 35-45 year age group. This personalisation leads to more conversion and sales. 

Secondly, analytics powered by AI & ML marketing model helps in providing real-time data analysis and forecasting to users. This allows marketers to align their campaigns to the changing preferences of customers. Pattern identification is another critical feature of these marketing models. This helps in identifying customer mass with the same behaviour and user patterns. 

Varied use cases:
Increasingly, multiple sectors are tapping marketing analytics to design and implement their marketing initiatives. Historically, retail & CPG (consumer packaged goods) has been avid user of this technology application. “Leveraging analytics, the retail sector is executing budget allocation and optimisation-based portfolio growth. As the selection of channels is vital for driving growth in this sector, marketing analytics is helping companies to choose the right channel apart from enabling scenario builders for multiple outcomes. In many ways, data analytics is at the forefront of digital transformation of the retail sector,” Pandey, co-founder & CEO of Skewb Analytics, said. 

D2C (Direct to Consumer) & e-commerce are the other sectors, heavily using analytics-driven solutions. Identification of customer patterns along with the generation of LTV (lifetime value) are the tasks that are accomplished through these applications. Marketers use this insight to work out their thresholds in the cost of acquisition. This is critical for becoming profitable in a fiercely competitive e-commerce space.

The automobile industry is increasingly using marketing analytics a lot for its portfolio management and targeted marketing campaigns. Managing the dealership ecosystem is the singular factor that determines the success of any automobile player. Analytics helps automobile players seamlessly manage the dealership ecosystem. Realtime optimisation of the number of vehicles to be sold in any given time period helps companies to identify the focus areas. They also determine where to spend more money, whether on mass media advertising or behind dealership items like trained sales force, promotions, and discounts, among others. 

Given the favourable outcomes drawn from leveraging marketing analytics, many other sectors like telecom, consumer goods, F&B (food& beverages), hospitality, and tourism, among others, have started using marketing analytics. No wonder all these sectors are reaping the benefits of analytics for various functions and improving their profitability. 

Many emerging technologies are transforming the way enterprises reach out to their prospective customers. And marketing analytics is ruling the roost. Especially predictive analytics is seeing rapid adoption among enterprises. “In the current macroeconomic environment, when the world is going through a slowdown, businesses are looking at ways to save costs and improve profitability. In this context, marketing analytics can be a great tool to achieve these objectives. Therefore, businesses should collaborate with the right technology partners to stay ahead of the competition,” Pandey, Cofounder & CEO of Skewb Analytics, said.