Retail should be dataSmart!

Reaching out to the right customers at the right time is very important in the retail industry. With the rising cost of real estate, manpower, transport etc, running retail stores have really become a challenge. Natural footfalls are not sufficient to make a store profitable anymore.


While most of the retail stores have ‘loyalty cards’, ‘reward points’ ‘promotional offers’ etc, few are able to use customer data intelligently. We know, Loyalty points aren’t too exciting and promotional offers are also too generalized.
I would share a personal experience. I had purchased some ‘dresses’ for a new born baby in December 2012 from a well known retail giant X. After that also, I have shopped for number of baby items like pram, dresses, feeder, rocker etc. but all from different retailers. The retail giant X could get all information about me and my purchase when I visited their store first. They could have sent me relevant offers based on this data. If I had received a tweet/ call from the retailer in March (that is when I bought a pram from a rival retail stores). “Howdy, how’s the baby doing? Now since the baby is 3 months old would you like to try some of the exclusive collection of prams we have in our stores? We offer you a 5% discount too”. I would have just loved this offer. Toys, books, walker, cycle, play mat, games the list is endless all offered at different stages as the baby grows.
Similarly, If someone comes to buy a ‘walking stick’ or ‘adult diapers’ chances are he would need other products too meant for the elderly. Idea is to draw valuable insights from data, to know the customer & his behavior better and then do a more targeted positioning of products. This is where Big Data, Traditional & Social CRM could really help the retail industry. Marketing augmented by data insights could add a lot of value.Want to know more? Give me a shout!

About the Author:
Sanjay Abraham is an Enterprise Social Consultant. He comments & blogs on the Enterprise Social Space on regular basis.

ImageHe also provides consulting & training to organizations in Social Media Marketing, Social Commerce, Social Business, Social Intelligence, Big Data, SoLoMo and other topics.
Sanjay holds a Bachelors in Engineering (Computer Science) and a PG Diploma in Business Management. He has worked with top names in the IT sector like Avaya GCL & Mahindra Satyam.  His client list includes top bracket names across Banking, Insurance, Retail, Public Services and other verticals. Consulting & Business Development through ‘Solutioning’ are his personal areas of passion.

Linkedin: Twitter: @asanjay100

Analytics- a game changer for Telcos (CSP)

ImageIndia has around 900 million mobile users which is second largest in the world.   An interesting fact about India is while most of the countries have maximum 2-4 telco operators, India has around 12. Also unlike US & UK, the prepaid customers are quite large ( around 90%) of the total customer base.

While the market is huge, with number portability allowed now, Customer churn is a major pain. Customer poaching is on and retention is a big uphill task. Tough competition, depleting customer base and plummeting margins are real challenges for this industry.

CSPs are generating large volumes of data, including  call data, network data, location data and customer data. Also no other industry in India has its IT ecosystem as complex as the Telcos.  They have scores of OSS and BSS like Network Monitor System, CRM, Billing system etc. The contact centers have their own separate set of software. The social media too has emerged as a big data source.

Analytics could be a real game changer for this industry. Like, Call detail record (CDR) could give important information about customers “usage patterns”. ‘Who’s calling whom’ etc. could help in better customer centricity. Analytics could also help in monitoring the call drop rates on the network for better maintaining the networks and reduce customer churn.

Analytics on this avalanche of data could help a lot in offering ‘right’ packages to the customers. The prepaid customers usually recharge for as low as Rs. 10 ( 1/6 of a USD), they change the CSP quite often based on offers they get. This customer base though being huge, is quite volatile. If a prepaid customer is ‘burning’ his minutes fast its likely he is about to move to other CSP .Big Data analytics could help in offering better deals and retain such customers.

Value Added Services (VAS) could bring greater revenues if analytics is used. All CSPs have offers like  ‘discount vouchers ( at eateries, travel, gym-spa etc) but are these offers based on customers data like his location, interactions with contact center, likes & comments on social media etc. News/ consultancy/ contents like devotional, sports, entertainment etc  too could be curated, customized based on personal interests. Presently all are ‘ spray and pray’ offers. The approach of CSPs is to offer them to all subscribers…may be some like it.

CSP are facing pressure to reduce costs and maximize average revenue per user (ARPU), Fact of the matter is, the idea of ARPU has lost its sheen across the globe today. It makes more sense to use ARPA (Average Revenue per Account) in today’s context. Deals for the company, Family, Community etc makes much more sense. Big Data Analytics could help in offering ‘smart’ group packages.

Contact Centers are the fulcrum of customer service in Telcos.  I have done ‘Agent Shadowing’ in number of call centers to identify the impeding factors in the agents works & processes. One of the pain point is that they have to toggle through multiple screens while they handle calls. Big Data analytics could directly improve call center metrics like AHT (Average Call Handle Time), ACW (After Call Work) etc by presenting consolidated ( single screen) view of information to the agents which is spread across multiple applications in the organization. All contacts these days have ‘call and data loggers’ which record data & voice. Analytics on these data could help in assessing agent performance and provide better agents training & improved customer services too.

Analytics could add lot of value to this industry.