MediaMath

THE BOTTOM LINE

MediaMath deployed IBM Netezza to support its online digital media platform that helps clients track and manage their online advertising. In examining this IBM Smarter Commerce project, Nucleus analysts found Netezza enabled MediaMath to improve its marketing, customer service, and sales processes to sustain its triple-digit annual growth rate while managing technology costs.

ROI: 212%

Payback: 5 months

Average annual benefit: $2,248,000

THE COMPANY
MediaMath provides technology and services to help its clients make rapid, informed decisions about where to place investments in online advertising, such as banner ads and search engine results. The company’s demand-side platform, TerminalOne, brings together data, digital media channels, and analytical algorithms in one interface so marketers and ad agencies can measure and plan the best mix of ads based on their target customers and Web site traffic dynamics. Founded in 2007, the company is based in New York and has approximately 140 employees.

THE CHALLENGE
MediaMath’s clients are budgeting for banner advertising, search engine hits, ads on social networking sites, and other digital media. They are typically charged a fraction of a cent for each thousand users that view their ad. The price is set by competitive bidding, and MediaMath helps them determine the advertising and media mix that will deliver the best results.

As the volume of traffic on the Internet grew, so did MediaMath’s customer base and the volume of transactions MediaMath’s platform needed to manage. At the same time, digital advertisers were becoming more sophisticated and demanding that more complex analyses be delivered faster. MediaMath rapidly outgrew its initial MySQL environment, and found that by mid-2009 its investment in Oracle Standard Edition Database with five terabytes of data couldn’t support the 350,000 daily transactions MediaMath’s customers needed it to analyze. MediaMath determined it needed to look for a technology that could scale to support the growing needs of its business and could be a competitive differentiator in the rapidly-evolving digital advertising marketplace.

THE STRATEGY
In September 2009, MediaMath started looking for a solution and explored data warehousing and analytics technologies from a number of vendors. All the vendors were invited to compete in a test case, and only Netezza and GreenPlum were able to successfully meet MediaMath’s requirements. Ultimately, the company chose Netezza because it felt more comfortable investing in technology from a publicly traded company, and because Netezza’s appliance approach would be less costly than other options.

Because Netezza consultants had already built an appropriate data model for MediaMath as part of the competitive test case, MediaMath was able to use that to accelerate the deployment and avoid any additional consulting costs. It took an internal team of five people approximately two weeks to deploy the Netezza data warehouse appliance and Netezza Analytics. Today, Netezza supports analysis of more than 13 billion advertising impressions a day.

KEY BENEFIT AREAS
By moving its platform to Netezza, MediaMath was able to improve performance and market its analytical capabilities as a competitive differentiator, increasing both the volume of customers and the number of transactions it had to manage. Key benefits of the project include:

• Improved service delivery. Moving to Netezza has enabled MediaMath to provide more rapid and sophisticated analyses to clients so they can make better decisions on their media spend.
• Scalable growth. By increasing the speed and complexity its analytical platform can manage, MediaMath has been able to perform better targeting for its clients and drive down their average cost of acquiring a customer, enabling MediaMath to continue its triple-digit year-on-year growth rate.
• Reduced technology costs. Adoption of Netezza has reduced MediaMath’s annual spend on software license maintenance as well as enabling it to grow without adding IT resources to support its business.

BENEFITS
Direct 100%
Indirect 0%
TOTAL 3-YEAR BENEFITS: $6,636,000

KEY COST AREAS
Key cost areas for the project included hardware and personnel. Netezza consulting was not needed.
Hardware 32%
Personnel 68%
TOTAL 3-YEAR COSTS: $1,614,000

BEST PRACTICES
MediaMath is an example of a company that delivers sophisticated analytics as a service and Netezza was critical to its ability to deliver the expected product to clients. Given the relative immaturity of the technology, MediaMath used a competitive test case to evaluate which vendor could deliver in terms of performance. Once the technical demands were met, MediaMath looked at the business impact and risk associated with each vendor. This strategy enabled it to select the best technical partner, engage the partner to show how the technology could be optimized for MediaMath’s needs, and ultimately select the partner that was most likely to suit its short-term technical and longer-term business needs.

In services businesses, companies must sell by differentiating what they provide as better, faster, or cheaper than the competition, and then deliver on that promise.
Deploying Netezza enabled MediaMath to use its analytics capabilities not just as a differentiator in the sales process, but as a cost-effective means to deliver its service to customers.

CALCULATING THE ROI
Initial and ongoing costs calculated for the project included MediaMath’s investment in Netezza Analytics and the personnel required to deploy and support the solution.
Direct benefits quantified included the net annual software licenses costs associated with retiring MediaMath’s existing Oracle database deployment and a conservative estimate of the additional hardware, software, and personnel costs MediaMath avoided that would have been required to reach the same level of performance from expanding its Oracle database environment.

DETAILED FINANCIAL ANALYSIS

SUMMARY

• Project: IBM Netezza
• Annual return on investment (ROI) 208%
• Payback period (years) 0.46
• Average annual benefit 2,212,000
• Average annual total cost of ownership 538,000

ANNUAL BENEFITS	Pre-start	Year 1	Year 2	Year 3
Direct	0	2,292,000	2,172,000	2,172,000
Indirect	0	0	0	0
Total Benefits Per Period	0	2,292,000	2,172,000	2,172,000
DEPRECIATED ASSETS	Pre-start	Year 1	Year 2	Year 3
Software	0	0	0	0
Hardware	450,000	0	0	0
Total Per Period	450,000	0	0	0
DEPRECIATION SCHEDULE	Pre-start	Year 1	Year 2	Year 3
Software	0	0	0	0
Hardware	0	90,000	90,000	90,000
Total Per Period	0	90,000	90,000	90,000
EXPENSED COSTS	Pre-start	Year 1	Year 2	Year 3
Software	0	0	0	0
Hardware	0	20,000	20,000	20,000
Consulting	0	0	0	0
Personnel	24,000	360,000	360,000	360,000
Training	0	0	0	0
Other	0	0	0	0
Total Per Period	24,000	380,000	380,000	380,000
FINANCIAL ANALYSIS	Pre-start	Year 1	Year 2	Year 3
Net cash flow before taxes	(474,000)	1,912,000	1,792,000	1,792,000
Net cash flow after taxes	(462,000)	1,001,000	941,000	941,000
Annual ROI - direct and indirect benefits				208%
Annual ROI - direct benefits only				208%
Net present value (NPV)				2,018,604
Payback (years)				0.46
Average annual cost of ownership				538,000
3-year IRR				205%

FINANCIAL ASSUMPTIONS
All government taxes 50%
Discount rate 8%