Thomas Freidman’s The World is Flat made the case for globalisation, rewriting the rules of competition by focusing on Silicon Valley entrepreneurs such as PV Kannan, co-founder and CEO, 24/7 Customer, who set up the first BPO outsourcing operations in India.
In an interview, the California-based entrepreneur shed light on how his firm helps companies deal with customers in the age of Twitter. According to him, companies can use predictive sales software based on advanced mathematical models with online chat to convert people trawling through websites into serious buyers. Excerpts:
Companies are sifting through gobs of digital data that customers feed networks while working, chatting and shopping online to build businesses. How does 24/7 Customer use data and mathematical models to help customers increase sales?
On any given day, big companies receive millions of hits on their websites and the conversions are still fairly low. Visitors come for different purposes, to buy products, or get answers about a purchased product. Can we predict the intention of a visitor to a website? That is the layer that we are peeling with data and mathematical models.
We see a message in a click. If a customer spends two minutes looking at a luxury watch and lives in a rich neighbourhood or zip code, it signifies something. 24/7 Customer is also working on predictive customer service, doing data modelling on customer behaviour, so firms know the issues a customer is likely to have, say, within the first 72 hours of purchasing a product.
One of our business units, 24/7 Innovation Labs, has created models that enable real-time prediction of customer behaviour. It used statisticians to develop advanced mathematical models to predict how visitors to the Adobe Systems website would shop.
They mined data on website traffic, product average order value and online behaviour, which helped to create models that predict who will need assistance, when they will need assistance and then trigger an intervention with a chat for those customers that need help. It offers a way of converting browsers into buyers. Adobe has been using SalesNextT for a year with great results.
We have 14 customers, who use what we call our modelling software; some of those clients also use our online and call centre services.

Thomas Freidman’s The World is Flat made the case for globalisation, rewriting the rules of competition by focusing on Silicon Valley entrepreneurs such as PV Kannan, co-founder and CEO, 24/7 Customer, who set up the first BPO outsourcing operations in India.

In an interview, the California-based entrepreneur shed light on how his firm helps companies deal with customers in the age of Twitter. According to him, companies can use predictive sales software based on advanced mathematical models with online chat to convert people trawling through websites into serious buyers. Excerpts:

Companies are sifting through gobs of digital data that customers feed networks while working, chatting and shopping online to build businesses. How does 24/7 Customer use data and mathematical models to help customers increase sales?

On any given day, big companies receive millions of hits on their websites and the conversions are still fairly low. Visitors come for different purposes, to buy products, or get answers about a purchased product. Can we predict the intention of a visitor to a website? That is the layer that we are peeling with data and mathematical models.

We see a message in a click. If a customer spends two minutes looking at a luxury watch or life insurance rates and lives in a rich neighbourhood or zip code, it signifies something. 24/7 Customer is also working on predictive customer service, doing data modelling on customer behaviour, so firms know the issues a customer is likely to have, say, within the first 72 hours of purchasing a product.

One of our business units, 24/7 Innovation Labs, has created models that enable real-time prediction of customer behaviour. It used statisticians to develop advanced mathematical models to predict how visitors to the Adobe Systems website would shop.

They mined data on website traffic, product average order value and online behaviour, which helped to create models that predict who will need assistance, when they will need assistance and then trigger an intervention with a chat for those customers that need help. It offers a way of converting browsers into buyers. Adobe has been using SalesNextT for a year with great results.

We have 14 customers, who use what we call our modelling software; some of those clients also use our online and call centre services.