CQuotient was founded in 2010 with the mission of helping retailers infuse customer insight into every decision they make.
To grow same-store sales in today’s retail environment, you need to convince your customers to spend more with you than with the competition. And to do so, you need to understand your customers better than your competition does and systematically act on this understanding. Most marketers would agree with this as a basic tenet of retail. And with the onslaught of Big Data, the opportunity to understand your customer has never been greater and the urgency to do so before your competitors never more acute!
But there’s a striking gap between the belief in this tenet and capabilities to live up to it. Many retailers know very little about their customers, and even less about how speak to them in compelling ways. This is because customer insights you can act upon do not come from the copious sales/inventory reports you get from your enterprise systems. Nor from monthly reports you may get from third-party panel data providers. Nor from website analytic tools that describe browsing behavior, but not cross-channel shopping behavior.
Rather, customer insight comes from deep, systematic probing of all these data sources – and more! -while keep the customer as the key organizing element. Think “Big Data meets CRM” and you get the idea.
Unfortunately, there is nothing in the way of analytic technology that helps cross channel retailers systematically understand, target and earn greater spend from all their customers. Certainly there are traditional Direct Marketing tools, but these are not up to the task in today’s world of Big Data. The amount of data is too overwhelming, the diversity of data is too great, and the analytic, technical, and operational challenges of putting this data to work for all your customers across all channels is simply too complex for traditional tools and techniques.
This is why CQuotient was founded.
Our technology takes in numerous data sources – offline and online transactions, visits, product details, store details, promotions, geo-demographics, web browse data, social data, mobile usage, email interactions, etc. – and uses them to decode every customer’s unique tastes. How they shop, where and when they shop, what merchandise they like and don’t, how price sensitive they are, what offers they prefer, etc.
Armed with this unique understanding of what drives each customer’s behavior across all channels, the software systematically tailors marketing programs to each customer using those levers. The result is more relevant marketing that engenders increased loyalty and increased spend per customer per year.
Is there a retailer out there who doesn’t need this to compete with Amazon?