How Tamr Removes a Massive Barrier to Data-Driven Marketing
A recent Infogroup study unearthed a deep pain point for marketers chasing the big data promise of a 360-degree customer view: they don’t trust that their customer data is ready for the analysis it deserves.
Infogroup’s “Big Data’s Big Payday” report found that just 21% of the ~600 marketers surveyed at the 2014 DMA Annual Conference & Exhibition said they are “’very confident’ in the accuracy and completeness of their customer profiles, and 15% said data collection will be their biggest data-related challenge this year, following only analysis (21%) and application (16%).”
It would appear that this lack of confidence has become a barrier to fulfilling one of big data’s most valuable use cases – personalize marketing campaigns. According to Infogroup:
When asked what stands in the way of implementing personalized campaigns, marketers blamed difficulty integrating across channels (40%), lack of quality customer data for segmentation (35%), and fragmented systems (32%).
Customer data is among an enterprise’s most valuable assets … nothing less than high-octane fuel for customer sales, retention and service. Understandably, the number of marketers investing in data-driven marketing is accelerating – from 54% in 2013 to 62% in 2015, according to Infogroup.
The problem is, the systems that marketers have invested in for capturing customer information are often dedicated to single functions or geographies – creating the very data fragmentation, quality and integration barriers that Infogroup’s marketers blame for limiting usage. Historically, data silos in the enterprise have been difficult to unify, causing a large bottleneck for downstream analytics and applications. Traditional ‘top-down’ approaches of standardizing enterprise data just can’t deal with the scale of data variety found in today’s enterprise. And this is before marketers even begin to account for external customer data sources like social media, 3rd-party data sets, etc. – which only expand segmentation and personalization possibilities.
The bottom line: the volume and variety of internal and external marketing data available to the modern enterprise is enough to choke traditional top-down data integration and preparation systems. So data marketers end up doing something entirely rational in this context: take what data they think their system can handle and leave the rest for another day.
That day has come – brought to you by Tamr.
Tamr’s Customer Data Integration solution flips the traditional top-down approach on its head, using a bottom-up, probabilistic model reminiscent of Google’s solution for web search and connection.
- Tamr’s machine learning algorithms perform most of the work, unifying up to 90% of customer sources, attributes and entities (names, addresses, demographics, emails, etc.) without human intervention.
- When the Tamr system can’t resolve connections automatically, it calls for human expert guidance, using people in the organization familiar with the data to weigh in on the mapping and improve its quality, integrity and speed.
- RESTful APIs then deliver a consolidated view of customer information wherever your analysts need it: from spreadsheets to business intelligence platforms and next-generation analytic tools.
The result of Tamr’s Customer Data Integration solution? A unified, 360-degree view of internal and external customer data that’s prepared for analysis (like demographic and behavioral segmentation or predictive analytics) and applications (like sophisticated cross-selling and personalized marketing) that can accelerate any enterprise’s return on their big marketing data investment.