The Challenges of Being Big
Large enterprise environments are rarely beautifully structured and perfectly scaled in line with business needs. For many, becoming large is a direct result of M&A activity and this growth results in an inevitable inheritance of new or additional systems. More common, a large data environment is one that is often disjointed, supporting multiple systems and CRMs and other important data silos across lines of business. This was certainly the case for one of the largest US Banking and Financial Services companies that contacted Squirro to help it gain a 360-degree view of their clients.
Following their own period of growth and acquisition, the Bank struggled to make best use of their client data nationwide as it resided in silos across 19 different CRM systems. This meant a client manager on one line of business had no exposure to what other products, services or history their client may have in dealing with another side of the business. Commercially, the set up was not at all compatible with maximizing opportunities for cross-sell and upsell. For clients, this made for a fractured and dissatisfying experience. Something had to be done.
Search Without Searching
Squirro worked with the Bank as a core infrastructure layer was implemented, taking in some 20 different lines of business. Squirro’s platform allows for the search of both structured and unstructured data, to ensure all pertinent information – whether internal or external, is accounted for in generating insights and results for users. This provided the basis for key account teams to achieve their goal of creating an adaptive and unified view of clients through Squirro’s Cognitive Search solution.
Traditional Enterprise Search solutions fail users for a number of reasons. Firstly, it presumes the user will know the appropriate keyword(s) to search for the results they need. Frequently, users don’t know the most relevant terminology used when a document was created, so results are less than relevant and still demand a manual ‘sifting through’ by the user to determine what’s useful.
Squirro’s Cognitive Search turns this notion on it’s head – instead of the user searching for the most relevant information – the information comes to them, automatically. It does this by cognitively ‘understanding’ the user’s context and informational needs, the data sets available and provides a mechanism to match both efficiently and effectively.
Squirro’s catalyst detection functionality allows it to achieve this understanding of what a document is about, and learn from user interactions and work flows of that document. This forces results through a lens of relevance for the user. For example, it will understand a user is searching for ABB (an engineering company) and won’t pull in information that is similar in keyword terms – but miles apart in relevance – such as #abb, a teenager discussing youth issues on Twitter.
Empowering Engagement, Driving Opportunities
For the 12,000 nationwide relationship managers at the Bank, the benefits are clear. They can search their clients with confidence, knowing all relevant information is accounted for across all lines of business. Managers now have much more time to spend engaging with their clients, rather than searching for additional information about them. What’s more, their cognitive searches can be saved or shared with team members, and continue to evolve with new data sources and interactions. With full client exposure across lines of business, relationship managers can quickly identify opportunities for cross sell or upsell and deliver the service clients expect.