Causata Targets Your Marketing with Predictive Analytics
Considering the growing popularity of mobile and the cloud, Causata – a big data analytics provider – is on to something special: their identity graph technology allows companies to connect with their customers in a more personal, targeted manner. Causata’s VP of Marketing Brian Stone joined us for a discussion on the challenges of the increasingly web-oriented business workplace and the unique role Causata fulfills in B2C marketing analytics.
To learn more about Causata, please visit their website.
LOCATION: San Francisco, CA
What is your mission?
Our mission is to help B2C companies create meaningful experiences through data. The technology delivers the right experience and context to the right person.
Big Data is a hot segment, so what inspired you to found Causata?
The company was founded in 2009 by former Touch Clarity executives. Touch Clarity was a real-time web personalization specialist. The vision was that consumers these days deserve a better, more personalized experience across multiple channels: mobile phones, the web, social, call center. They should be treated as individuals that companies know something about as opposed to being a generic member of a segment.
So what do you do differently in this space?
We do three things. We have an ability to create an individual customer profile by stitching together all the different interactions that a unique individual has with a company. Once created – we call it a “Causata identity graph” – we’re able to predict a customer’s intent. So we do predictive analytics and modeling, integration to modeling tools, and through the formation of this predictive profile we’re able to make real-time decisions across various channels. Whether that’s delivering content over the web or through email, or even just creating a personalized interaction through a call center, our solution turns big data into customer insights and decisioning for when it matters most.
What do you do to make sure you stand out from all the industry noise around Big Data?
We’re building industry-specific analytic applications for cross-sell and retention. That’s a fancy way of saying: on top of this sophisticated Big Data infrastructure that we’ve built, we’ve developed apps for financial services, digital media, communications, and more. They’re all focused on customers or predicting the probability that customers are open to cross-selling or likely to churn. In financial services that might be called share of wallet or balance consolidation. In communications that’s churn. In digital media that’s subscription acquisition, renewals, and up-sell.
Where do you find your customers? And what would your ideal customer look like?
We have a series of alliance partners in the business intelligence space. But we also do typical lead generation and relationship building. Our average sales cycles are 6 months. They’re enterprise sales – we’re selling multi-channel decisioning. We’re most active in financial services and digital media, as I mentioned.
How is Causata set up: where are your offices, teams, and customers located?
We have our engineering and development office in London, consisting of 25+ folks. Sales, Marketing, and Services are mostly in the Bay Area with a few in New York. We have a little over 50 employees in total. Our customers are mostly based in North America. We have about 10 customers ranging anywhere from proof of concept to being in deployment to being live on the system.
Where is Big Data headed? Where do you see it in 5 years?
Let me give you a two-part answer. Today, Big Data really revolves around analytics and IT. But 5 years from now, Big Data will be a Marketing or line of business tool. I don’t think it will be called decisioning – we’d like to refer to it as “brand relationship marketing” – but it’ll essentially be a way for marketers to have their brand better interact with customers on a personalized basis. It’s impossible to do that today. If you name a brand that you interact with on a frequent basis, that understands you, predicts your intent, and delivers the right offer or content to you at the right time – someone who instills loyalty as a result of their interaction with you – you will likely think of Amazon. They are very good at delivering personalized experiences over the web, and that’s where the market is headed.
What challenges do companies looking to tackle Big Data face and how can they overcome them?
There’s one enormous challenge that’s very hard to get around: the customer data prison. The problem is that Fortune 1000 enterprises over the last decade have invested significantly in data warehouses and modeling tools. Their data is captive to that technology. Not only can they not get the customer data out in a timely fashion, but they can’t connect it, make sense of it, and turn it into valuable insight that they can act on. These companies are spending so much money on new solutions to help them with their existing problem it has become like a drug: they can’t stop spending money, they’re on maintenance, and rather than resolving the customer data prison, they’re magnifying it. What we’re advocating is to get out of the data warehouse. Move to a next generation, non-relational data repository like Hadoop and run a series of analytic applications from Causata against this data to generate insights and decisions.
Why is Big Data so popular right now?
With the advent of mobile – starting in earnest 3 years ago with the iPhone – and adding social to the mix, people’s buying behavior has changed. It used to be that companies sold things – now customers buy things; meaning, we make up our mind before we ever talk to a sales person. So vendors looking at all this data from mobile, social, and web applications need to make sense of their customers and predict their intention. Otherwise, how can they deliver a meaningful experience to their customers?
What is the most exciting thing about Causata?
We think there is a multi-billion dollar opportunity here for customer experience applications that will build on CRM in the future. We don’t know exactly what it’ll look like or what it’s going to be called in the future, but whoever cracks the code on delivering meaningful experiences to customers can create a very successful business.
Who are the most interesting companies in technology today and why?
The obvious one is Apple, because of the experience they deliver. Amazon is somewhat obvious, because it’s not just their recommendations engine, but also their Web Services and the cloud business they have built for enterprises in general. And the third company we think is really a model in terms of what they’ve done is Splunk. They took a very specific problem – IT logs and infrastructure management – and used Big Data analytics to streamline it.
Looking for more information on big data? Check out our side-by-side comparison of leading platforms in the Top 10 Business Intelligence Software report. You can also browse exclusive Business-Software.com resources on the subject by visiting the business intelligence research center.