Putting Your Data to Work
Over the past decade we’ve seen an explosion on two fronts. The first is the digitization of business processes and engagements, with an exponential increase in the data created and logged across systems. And the second is the emergence of a new category of visualization tools, putting power in the hands of data analysts to explore and gain insight. All of this has created an opportunity for companies to build a new level of understanding of their customers, and use that to improve their products, service, and support and to increase customer loyalty.
This isn’t news. Companies have recognized this shift and have invested accordingly, and this trend will continue. In fact, according to a recent HBR article – Why Marketing Analytics Hasn’t Lived Up to Its Promise – the percentage of marketing budget dedicated to analytics is expected to triple from 5.8% to 17.3% over the next three years. And that doesn’t count the additional investment IT departments are making in infrastructure to support analytics in their internal data systems. The challenge, as noted in the article, is how to get the most value out of these systems.
What we’ve observed in our discussions with customers is that all of these investments are only as good as the quality of the data that powers them, and the capability and training of the people who use them. Whether it is analytics, demand generation, or customer experience, every model and every scenario starts from the premise that it is working with high quality data, and has been created by someone who understands how to use that data. In other words, you’ve got to put the right data in the hands of the right people, and give them the tools to do their best work.
In order to do this, we believe it is critical to have a customer data platform that builds on the data investments companies have made, takes in all the data, generates a unique view of the customer tailored to the business needs of a company, and unlocks the full power of modern systems used for analysis, demand generation, and engagement.
Take in all the data. We think it is critical to take the data in raw, in as native a form as possible, so as we learn more we can adapt. The reason this is important is that it allows for flexibility and iteration that adapts to the changing needs of a business. Many companies take an approach of building connectors to data, so instead of taking your data as is, they force it into a schema or model that they understand. While this works for a given area or use case, it makes it very challenging to adapt and change as you learn more about what you need. It also prevents the opportunity to take additional signals from the data that can be used to increase matching for identity resolution or add new semantics to the customer profile.
It is important to note that any system has to build from where a company is today. Significant investments have been made in systems – from data warehouses to digital transaction systems to eCommerce and more. This work must inform any approach to generate a holistic view of a customer.
Stitch it together. The next step is to use modern machine learning techniques to stitch the data together, creating a single view of the customer that spans all of the disparate systems. This approach enhances and builds on any investments that have already been made to unify data – whether in the form of a unified key across data systems, an enterprise data warehouse, or other integration systems. Unlike other systems that use deterministic models with a predefined schema to bring data together, our system adapts to the information that is unique to your dataset and creates connections that can only be determined through the processing available in today’s commercial cloud platforms. Our approach delivers a full customer 360 profile, that includes all the data about a customer as well as custom calculated fields that apply uniquely to a company’s business.
Make it available for analysis, engagement, and insight. Next, the data must be made available to the latest modern systems for analysis, engagement, and insight. Companies have invested years in training marketers and analysts on world-class tools – from data visualization to campaign management to customer experience. They don’t need new systems, they need these systems to have better data. So our focus has been to bring the data right to these systems, and build on the investments that companies have already made. We can do this because we build on the power of the public cloud, and allow marketers and analysts to use a simple web interface to create exactly the right data to power their tools, in a format that is tailored to ensure maximum performance and scale.
Design for rapid iteration. Finally, we think modern customer data platforms have to be designed for rapid iteration. We live in a changing world, with new data sources coming online, acquisitions and mergers bringing companies together, and new tools coming to market. Systems can no longer just be resilient to change, they must embrace it. That’s why our customer data platform is designed from the start to adapt. In our first 90 days of any engagement with customers – we work with them starting from their business objective, helping identify the right data, and then implement a solution that connects their data to the business objective. We think it is critical to demonstrate the business outcome as we go. From there, we make it easy to do more. You can add a new data source and produce a new view of the customer, while still maintaining the old view for systems that rely on it. You can connect a new source and increase discovery of linkages between records, and then apply that knowledge to all of the existing engagement and marketing systems. And you can onboard data from a new company or acquisition without requiring an expensive consolidation in the systems of record.
We’re delighted to be part of the transformation, led by passionate innovators at leading companies who are committed to doing more for their customers. We’re powered by the work and leadership of innovators before us – from public clouds to new tools for analysis to advanced systems for engagement and demand generation. And we’re optimistic that the work we do can make a difference and unlock data to the right tools so thought leaders can do their best work.