Last week Ogilvy announced a partnership with Marketshare Partners, a marketing science company based in LA with offices in NY, San Francisco, Chicago and London.  I had been looking for a while for a partner who could help us with econometric modeling, the type of analysis that can help you tie overall marketing spend to business outcomes and can help you determine how much to spend on marketing and how to allocate it by product, segment, geography and medium. 

I won’t go into the details of why Ogilvy chose Marketshare Partners or what the joint offering exactly entails.  This would not be the right place for it.  However I did speak to a lot of different companies in this space over the last couple of months and I thought I’d share my thought on how they differentiate from each other.  Hopefully this could be useful when you are looking for a partner - if you need one just give me a call

I started with laying out the various tasks involved with running an econometric modeling project that would result in a marketing investment strategy.  These steps are listed below.

Data Gathering : you need to collect data on marketing spend and performance from a wide range of sources.

Data Aggregation : you need to put all that data in one place where it can be accessed easily by analysts.

Statistical Modeling : you need to build the statistical models that link marketing spend to business outcome.

Optimization : you need to use those models to determine what the optimal marketing spend and allocation is.

Scenario Planning : you need to build several investment scenarios that demonstrate the impact of different investment strategies on business performance.

Dashboards & Management Systems : you need to give non technical users access to the data and scenarios through decision support tools.

Strategic Consulting and Planning : you need to help decision makers use these tools for decision making.

These are generally the tasks at hand when you run an investment optimization project that uses some science to get to the answer.  These tasks map perfectly to the market differentiators that started to emerge throughout my conversations with the various vendors.  This is illustrated in the diagram below.

Data Access : Some vendors had access to special data sources through alliances they had with 3^rd part data vendors or search engines.

Automated Data Preparation : Data preparation can use up a lot of your resources on projects like these.  Some vendors had automated a lot of these steps so that they could do the data gathering and aggregation described above faster, better and more cost effectively.

Unique Algorithms :  The algorithms have been around for decades so you would think all econometric modeling skills are pretty level.  However, you would be surprised how much variance there is in the quality of the statistical modeling between different vendors.  Make sure you look underneath the hood and talk to who is actually doing the modeling.

Decision Support Tools : Some vendors have packaged their tools in dashboards and scenario planning and decision support tools.  These tools can be extremely useful for helping the end users adopt some of the scientific evidence into their decision making.

Value Added Services : This is probably the most important area.  I have seen so many modeling projects collect dust on the shelf of the marketing intelligence managers.  Building models is easy.  Using them for decision making always seems to be the hardest.  You should always look for a partner who can help you with both.

Hopefully some of these learning can be useful for you at some point.  The reality is that far too few marketers are using econometric modeling to really understand the impact of their marketing efforts on their business.  As a result, they end up making multi-million dollar decisions on pure gut feel.  If there is anything this recession has taught it’s that that will ultimately get you into trouble!

The fourth chapter of the Math Marketing paper describes the current landscape of potential Math Marketing partners.

If companies need external partnerships to stay at the forefront of the Math Marketing revolution, whom should they partner with and what should they look out for? The Math Marketing partner of the future needs to be strong across three dimensions.

Broad Aperture
Math marketers must be able to look at the marketing landscape in its entirety. This includes all media and all elements of the marketing mix. They should understand the impact of marketing on overall business results. They also need the senior-level client relationships that can give them the authority
to take, and act on, this broader view.

Specialty Skills
Math marketers must have the specialty skills necessary to master the modern Math Marketing toolkit. This includes econometric modeling, data mining, statistics, Web analytics, online ad serving competencies, quantitative market research techniques, dashboard and visualization technologies, and social media analytics. They must always stay abreast of the latest developments in the Math Marketing industry; departments must also have the robust technical infrastructure to handle the large volumes of data involved in modern Math Marketing.

Access to Data
Math marketers need access to data. Traditionally, most data was owned and stored by clients. While clients still internally house the bulk of transactional and customer-level data, the digital era has seen other islands of data being created outside of clients’ corporate data warehouses. Microsoft and Google got in the ad-serving game with their acquisitions of aQuantive and DoubleClick, respectively. They are rapidly gathering online ad-serving data that can be used to optimize online ad spend. Online media agencies are investing in data infrastructures that enable them to get feeds from ad servers and store them themselves. Search engines have the most powerful source of search data for needs-based targeting. But very few companies have integrated this digital data with their customer data warehouses. It will be interesting to see in the next couple of years who will own what data and who will be creating the next-generation, single-customer views that will combine media exposure and interaction with search, website behavior with transactional and demographics data, all in one place.

There are various players in the Math Marketing area:

Media companies have always used mathematics to make decisions about investing media budgets. Most of them have econometric capabilities and are investing in ad-serving, data-warehousing infrastructures, which will allow them to mine that data for optimization and give them a considerable competitive advantage. They are predominantly focused on media decisions and have historically had a more transactional and less strategic view. This was usually reflected in client relationships, where media agencies tend to have less board-level access. This is changing rapidly, however, with media companies aggressively building their strategic capabilities. If they can attract the talent and own the data, they will be in a great position to answer the ROI questions of the future. However, there will always be the perceived issue of the “fox guarding the henhouse.” Clients will always have a suspicion that media agencies will favor recommendations that might benefit media agencies first.

Integrated communications agencies have traditionally had strategic relationships with clients through brand-planning teams. Some of them have built strong strategic services departments over the years. Teams like these will be able to take a broad view of ROI, and look at the impact of all 360 Degree marketing communications on a brand holistically. Their analytics teams also tend to have the technical skills to analyze large volumes of data. However, with new channels being introduced continuously, the teams will need to keep investing in new specialists who understand the inner workings of these channels well enough to use the data to answer the ROI question. (This technical knowledge might come more naturally for media agencies who know the details for media execution purposes.) Ogilvy’s strategic services group in New York, for example, is comprised of a team of 150 planners and consultants specializing in brand planning, marketing and digital strategy, and analytics. The integrated communications agencies usually get access to data through clients and partnerships with media agencies. Very few communications agencies store their own data, which could put them at a disadvantage versus others in the category.

Management consultants have entered the marketing ROI arena as an extension of their broader strategic services. For them, marketing represents perhaps the last area of expansion. By the very nature of what they do, they tend to take a broad and holistic view and probably have more senior client relationships than any other player in the category. This can give them the authority to tackle the marketing ROI question holistically. They are also often seen as more impartial than media and communications agencies. One of their main challenges is that they are often too far removed from the day-to-day execution of marketing campaigns, which means they often lack the in-depth technical knowledge of today’s marketing channels required to analyze ROI. Some of them are ramping up their services fast, though, as demonstrated by Accenture’s acquisition of digital multivariate testing company Memetrics in 2007. Management consultants usually do not have direct data access and therefore rely on clients to share data with them.

As mentioned earlier, Google and Microsoft entered the marketing effectiveness area with their acquisitions of the major ad servers in the industry. With the digitization of all media, they will soon hold the majority of all marketing effectiveness data. They have the capability to handle the largest volumes of data, and have mathematicians and engineers who, if focused on marketing effectiveness, could have the ability to do just about anything. They are not positioned strategically and therefore lack the broad aperture required to become real ROI partners, but they have the size and the financial power to change this quickly.

These main players will be supported by specialized companies to help them solve certain pieces of the overall ROI puzzle:

Agencies with a strong CRM and technology focus, such as Epsilon, Acxiom, Targetbase, Unica and Dunnhumby, have a great ability to mine high volumes
of customer-level data. Some of them also have easier access to data, as they tend to manage clients’ data warehouses. They have mastered the art of optimizing one-to-one communications, but they are almost never responsible for the entire marketing mix, which usually prevents them from looking at marketing ROI holistically.

Marketing research agencies help quantify ROI through surveys and panels. Since they are primarily the providers of research data and insights, some of them have developed extended ROI capabilities in brand measurement and econometric modeling. Millward Brown’s Optimor is a great example of such an extended capability.

Finally, there are analytics vendors who specialize in just one area of analytics. This category includes web analytics vendors such as Omniture and WebTrends; marketing mix specialists such as Market Share Partners, MMA and Hudson River Group; Financial social media analytics vendors such as Nielsen BuzzMetrics, Visible Technologies and TNS Cymfony; and many more. These players usually have partnerships with some of the players mentioned above and, in some cases, have even been acquired by them.

The diagram below summarizes the current Math Marketing landscape, with the main players plotted on a grid based on their ability to have a broad aperture and on their specialty skills.

A true ROI partner will have a combination of both and would therefore appear in the top right corner. No one is there at the moment. However, it is clear that the main contenders are management consultants, integrated communications agencies, media agencies, and Google and Microsoft.