AI-driven data analysis - The future of strategic marketing

Obidur Rahman a Bangladeshi data scientist and marketing tech expert who has innovated solutions catering to both local and international clients. He has developed AI-integrated marketing tools which can measure, track and predict factors such as customer engagement, rate of a product's success, impact in the market and trends in popularity based on customer profiling and regional preferences. These tools collect customer engagements in Facebook pages and use the data to chart marketing strategies for the respective brand. 

In a candid interview with Mr. Obidur Rahman, the current Group Business Director of X Solutions Limited & Founding CEO of iGroott, the tech hub of the marketing automation tools. Currently working on marketing solutions for 50+ brands he shared with us his journey as a data scientist and details regarding his two biggest AI-integrated marketing tools: Dotkom and Zerocium. 

Q: How did your journey into data analysis begin?

I joined a Grameenphone call centre in 2010. From there, I was able to join the social media online communication team. Around 2012, I began to proactively analyse the data in the Grameenphone database - customer behaviour, what kind of products people prefer, what services had the best social media engagement, etc. 

After getting an opportunity to work at Maverick Studios, who were doing a data-driven innovation drive for Robi, I decided to take a leap of faith. I left my established job at Grameenphone and joined Robi project as a data analyst, which back then was a completely new role in the local industry. Despite a shaky start, I focused on innovating solutions. After the official Facebook page for Robi was created, I created a tech based operational structure to track social interaction of the brand with its customers. It calculated metrics such as average interaction time, common point of interest and specific issues Robi could be struggling with. 

Using the innovated tech based operational capability, I had created an automatic business model. But just gathering data from Robi wasn't enough, as I needed to match the competitors as well. Thus, I formed the Robi Listening Centre, the first formal data analysis platform in Bangladesh. From there, I made a social listening tool called Social Troops, which kept track of other local telecom domain customers, monthly users, negative experience shared with Robi and any other data that was available from the Robi Listening Centre. Social Troops kept track of all this data as outbound and enabled me to create what I would say is our signature product: Dotkom.

Q. What is Dotkom? How does it work? 

Dotkom, an AI-centric social listening tool, is our flagship product. Launched in October 2021, this tool is able to scale the digital lifestyle of a customer by profiling their interactions with a brand's social media page. Unlike other language-processing AI, Dotkom is programmed to specifically pinpoint sentiments in the Bangla language, which can range from positive, negative or neutral comments left by customers in a brand's Facebook post. Based on what words have been used, the AI can understand if the customer has liked the specific service and if they might be interested in future offers.

The program utilises factors such as engagement ratio and value chain to filter data based on location. It is also able to filter fake complaints to save resource management and system misuse. Its language-processing capabilities enable it to find relevant and core problems being discussed by the customers, thus setting a priority management for managing public complaints better. 

Q. How does Dotkom perform market-based predictions?

Using data derived from customer comments, the AI creates profiles for each user and determines what socio-economic class they might belong to based on the regular pricing options of their availed services. Since there might be a noticeable difference in preference between, for example, 1 GB package buyers as opposed to regular 5 GB package buyers, the AI charts what needs are being addressed by the customers and how to provide better product management to specific classes of customers. 

Dotkom is also able to delegate and design new campaigns while measuring customer expectations. It keeps track of head-to-head comparisons of different products by the same brand and what the general opinion is regarding existing services. Using such sentiment-driven data, the AI can predict the success of a future product or service and offer more in-depth suggestions on how an upcoming offer can be advertised better. 

Q. Could you give us an example of how Dotkom might help a client brand? 

For example, if a 4G campaign by a telecom company is due release, Dotkom can pinpoint at least 10 reasons why that 4G campaign might produce an increase in negative sentiment by, say, 5%. The AI can then offer solutions to those problems by using data collected from customer profiles and previous problems that have been shared by customers via social media or customer care service. 

Q. Where is all this data available and how much maintenance is required?

Dotkom utilises publicly available data that is accessible at all times by anyone with a Facebook account. It uses the Facebook API, so complies to the legal rules and regulations.

Dotkom is automatically updated real-time without any manual input. It is completely run via an AI programmed by us and is currently used to provide telecom companies of Bangladesh with crucial data-driven predictions essential for their growth and success. 

Q. Regarding your other product, Zerocium, what is it and how does it function?

As a global joint venture Zerocium was developed by local and global resources with a vigorous capability to serve the needs of different brands around the world.  

Launched in 2021, Zerocium is the newer marketing tool which is an omni-channel solution catered towards making customer care service more efficient. Whenever a query pops up in Zerocium's shared network, the notification is seen by all the customer care agents of a company. A human agent from one branch can then cater to a customer who might be calling an understaffed branch. Zerocium is also able to keep detailed analysis of average response time for each customer, which agent served which customer and for how long and how fast a customer was satisfied. 

Q. How efficient is Zerocium?
Zerocium has reduced the average customer response rate to 1.5 minutes, where the global benchmark is 18 minutes. It always maintains zero pending customer requests and because of the AI-integrated query system, nearly 100% of the customers are served within the first 5 minutes of the call. The program is also able to send an automatic prompt that gathers information regarding satisfaction quota and user recommendations. Keeping track of the customer replies, the AI sends a detailed analysis to the respective company regarding resource allocation, customer engagement index and employee work rate.

Q. Is there any particular challenge you want to mention? 

Covid-19 was a challenging time for everyone. But I believe that challenge pushed me to work harder. Around May 2020, when the lockdown was at its worst, I made an IOT-based thermal thermometer of my own design. Back then a thermal thermometer was an expensive device and the supply wasn't available in the market, but I was able to make a simple one that kept track of the user's temperature, performed image processing and created a user profile. By scanning data in those profiles, I was able to surmise location-based infection density. 

While my initial intention was commercial, after I saw the public demand for my thermometer, I discarded the idea of a business model. I created a sample of 300 thermometers, and gave away all 300 for zero price, delivered using my own logistic system to whoever required it. 

I would like to add one more initiative where I created a virtual workforce for creating job opportunities for the unthought section who struggled during the Covid period. This one-of-a-kind platform presented job opportunities for almost 3000 people which I am really proud of as a socially responsible entrepreneur. And currently I am working on this to make it more robust and planning to launch it on a national level to create more job opportunities.

I have always wanted to solve problems using innovative technology, and being able to help even a little during a time of crisis motivated me to work harder, leading to the successful launches of Dotkom and Zerocium.