“The more I listened, the more I picked up on the fact that [the Tamr platform] really was different from what other machine-learning platforms are offering. It’s far more intuitive and match-driven, while at the same time being quite rigorous, quantitatively. — Vice President, Data Management and Operations, Media Company
Clean, trustworthy, and readily consumable data is essential to getting, keeping and growing customers. The problem: enterprises often can’t provide access to this kind of data fast enough for business analytics and operations nor at scale. This is because of the explosion and siloed nature of customer data and the limitations of conventional master data management techniques.
The Tamr Cloud-Native Master Data Management (MDM) Platform was built to solve this problem. It’s helping enterprises worldwide get a big payoff, by streamlining their data mastering operations, improving data users’ productivity, and opening up new avenues for downstream business growth.
To put the proverbial money where our mouth is, Tamr commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study1 examining the potential return on investment that enterprises may realize by deploying the Tamr Platform. Read the Forrester TEI study.
Based on conversations with existing Tamr customers, the study shows a “hypothetical” $15bn-revenue company that engages with Tamr over the next 3 years can achieve:
Nearly $9M in total benefits
Over $2M in increased profit due to access high quality customer data
$6.6M in increased productivity in sales, data engineering and analytics
A 70% and 80% reduction of manual efforts of data engineers and analysts
Business Challenges and Key Findings
Without clean and connected data, business users can’t make accurate business decisions and technical users can’t optimize data management, creating data sizzle–weak, distracting and hard to stick a fork into–instead of data steak. This is a problem across the enterprise, but the stakes are particularly high with data essential to acquiring and servicing customers.
Current Tamr customers interviewed by Forrester called out the following key challenges they encountered when using rules-based MDM solutions (or no solution at all):
Inaccurate or incomplete data, collected from multiple touch points with no established process to consolidate the data into a single record.
Data management inefficiencies, from the inability to consolidate, cleanse and categorize data at scale This process required heavy manual involvement from data engineers and analysts alike and slowed attempts to modernize MDM.
A business-velocity bottleneck.The organizations were unable to unify customer records to a point where the data could reliably inform business change and growth.
Using its time-tested TEI methodology, Forrester determined that an organization with roughly $15 billion in revenue using the Tamr solution can realize on average nearly $9 million in total benefits over three years versus costs of $1.18 million–for an ROI of 643% and a net present value (NPV) of more than $7 million.
The TEI study provides readers with a framework to evaluate the potential financial impact of the Cloud-Native MDM Platform to their organization’s customer data.
Here’s an idea of what you might expect from Tamr
Quantifiable benefits include:
Cost savings and improved productivity for data engineers, analysts, and sales representatives worth over $8 million: Using machine learning to conduct the heavy lifting of cleansing and curating data, Tamr reduces manual efforts by data engineers and analysts by 70% and 80%, respectively. With robust, golden records for customer profiles from Tamr powering systems like Salesforce, efficiencies are found for sales representatives too, estimated at a 30% time savings in dealing with data discrepancies that are applied directly to revenue-generating tasks.
Increased profit from additional opportunity creation worth more than $2 million: Before Tamr powered downstream marketing and sales systems, sales people had less time to dedicate to prospecting and directly interacting with clients because a significant portion of their day was spent on sorting through customer information. With Tamr providing access to clean, enriched customer data, each salesperson can generate 0.5 new opportunities per month and 10% of these opportunities convert into a deal. The organization has an average deal size of $15,000 for its B2B transactions.
Improvements to business topline, such as faster customer onboarding in financial services: Interviewees from both financial services organizations noted that using Tamr resulted in shorter customer onboarding times by at least 50%. This meant faster revenue generation for these organizations, as well as improved customer experience.
Also identified were a number of benefits not quantified by the study, including:
An improvement in data quality and trustworthiness, as business users started seeing reconciled and consistent records from a single source of truth.
An IT manager for a manufacturing firm said: “We realized we were clueless about who our customers were because our customer data was being collected in so many touch points and wasn’t being pulled together. [With the Tamr Platform], we were able to consolidate all the data and identify our customer, their needs and their information.”
A reduction in the number of data errors, as organizations moved away from manual customer data entry to ML-driven data reconciliation with Tamr.
Regulatory compliance based on access to a single source of truth, with lowered risk of errors in reporting due to manual data processing.
Prevention of their data lakes from turning into data swamps, through access to improved navigation across the ecosystems feeding these lakes and automated indexing and tagging of raw customer data.
“What we had [previously] was a data lake which was a dump of every customer record,” said the head of digital transformation in a financial services organization. “The data lake was not very utilized as a reporting aggregation because it wasn’t aggregating.”
The Numbers Behind the Results
The composite organization created by Forrester was based on the following key assumptions:
$15B annual revenue
10 million customer records
More than 5 different customer data sources
1,000 B2B-focused sales representatives
$15,000 average deal size
Customers interviewed by Forrester for the study came from multiple industries and managed anywhere from 4 million to 500 million customer records. Customers interviewed by Forrester for the report came from multiple industries and managed anywhere from 4 million to 500 million customer records.
For a full copy of the report, including Forrester’s detailed methodology2 , risk-adjusted PV costs, and more wisdom direct from the Tamr customers interviewed, go here.
To schedule a discussion with Tamr and learn how you might get this kind of ROI on modernizing your customer data mastering, click here.
1“The Total Economic Impact™ Of The Tamr Cloud-Native Master Data Management Platform,” Forrester Research, April 2021
2 The TEI methodology includes due diligence; customer interviews to obtain data with respect to costs, benefits and risks; creation of a composite organization; constructing a financial model framework; and creation of a case study to model the benefits, costs, flexibility and risks. Full details of the TEI methodology are available in the report.