Editor’s Note: This is a guest post from Deep Sherchan – Co-Founder and CMO at Simplify360, social business intelligence product where he shares his recent experience at the digital data analytics event conducted in Bangalore.
At sharp 2pm on 25th April, I was in front of HP’s Bangalore Office trying to spot HP’s employee who would guide me to the conference hall. Our reports on Indian Election buzz has been gaining lots of popularity and coverage from global media. In respect to that, I had been invited to give a talk on Impact of Social Media Analytics on Indian Election among the Digital Data Analytics community of Bangalore.
But beside my own talk, I was more excited about other speakers who were on the list which included Dell, HP, Flipkart and Redbus. As I entered the conference hall, I could notice the eager crowd tuned to a presentation being given by the speakers from Dell. Later, I was briefed that the crowd included data analysts from various tech and consulting companies like Adobe, HP, Dell, Cognizant, KPMG, Fidelity and Accenture. I would say, it was a vibrant and intelligent crowd.
The main theme for the day revolved around optimizing business functions using digital data captured through various customer touch points. Dell had much to showcase its technology and analytical prowess in handling big data and frameworks to enable teams to make real-time decisions. The core challenge was on how to connect all the online and offline customer data sets to drive meaningful insights. The presentation was very detailed and the audience had a lot to ask on analytical tools and methods being used.
The event had a flavour of experts and demonstration of knowledge sharing with eager passion to learn. This was more clear during the presentation of Redbus where the analyst was being questioned on various aspects of bus ticketing and the logistics involved – like what kind of data does Redbus use to predict the demand of tickets for a certain route and how is the logistics for this managed? Redbus team seems to be using lots of customer behaviour data sets to predict the demand. Even the logistics were being handled through their internal systems being shared with all the stake holders. It was great to see some real life applications of predictive analytics being implemented by Redbus and their focus on leveraging best of data to better their services.
My own talk on use of Social Media data sparked a certain debate on its usability and authenticity. I think the major issue which every one is currently facing with social media data is how to implement it in the core decision making process. For example, how can I improve my marketing campaigns using social buzz insights? The crowd had much to discuss even on the authenticity of the profile, like for example how much of buzz is created by fake profiles and so on? Time and again, I have always felt that the major doubt most people have is always on these two factors. Hence I demonstrated different methods employed by our team in Simplify360 to handle these issues.
Flipkart, on the other hand, had much interesting insights to share on the problem of locating customer densities in a city and devising a method to deliver the products quickly. The speaker hinted on the use of vans rather than bikes on certain region as a result of these insights. Moreover, Flipkart also pointed out to the immense challenge which an apparel product posed compared with other products, because apparel comes in a variety of shapes, sizes, colours, textures and brand.
Overall, the entire session had a mix of use cases of analytics in different business functions from customer acquisition to campaign optimization and logistic management.
For some years now, data scientists have been presented as the next big opportunity for job creation. But there is this big gap which I see between the job and the candidates. Most students are unaware of the existence of the field and different opportunities. But events like these on analytics is much needed right now to help businesses understand the power of digital data analytics and showcase its use cases.