Little Rock, Ark.-based Acxiom is the original data management platform. The 42-year-old company has arguably done more than anyone to blend online and offline data sources – for instance by helping automakers compile leads from their own branded sites, car research sites, dealer walk-ins, and other sources. Customers in financial services, media, CPG, and tech, among other sectors, have worked with Acxiom for decades and are entirely dependent on it to help manage their marketing data, both first and third-party.
Recent hires prove Acxiom’s digital seriousness. After tapping Microsoft/aQuantive vet Scott Howe as CEO last summer, it recently nabbed Nada Stirratt, a digital marketing exec with roots at MTV Networks and MySpace, as chief revenue officer. And this week it brings on Phil Mui, product lead for Google Analytics, as chief product officer (see release).
Mui is tasked with making marketing data accessible to the whole client organization, in the way Google Analytics has done for website data. On Friday, between goodbyes at Google, he articulated this plan in a discussion with AdExchanger. Acxiom CEO Howe also joined the call.
Click below or scroll for more:
- Data Viz And Company Strategy
- Acxiom’s Data And Service Layers
- Mui On Going From Google To Acxiom
- On The Exchange-Traded Media Space
AdExchanger: I want to ask about your background developing Google Analytics and shepherding that product along. Is there a similar plan to bring reporting and data visualization to Acxiom customers?
PHIL MUI: Scott’s vision for Acxiom is a direction Google Analytics could have gone down if Google didn’t care about the ability to store PII data.
If you look at ad exchanges, DMPs, DSPs, etc, there’s a huge amount of inefficiency in the marketplace. That’s why people have a hard time justifying very high CPMs, CPAs, stuff like that. The real challenge for Google Analytics and the digital side of the world is we are restricted to third party cookie data primarily when we try to help marketers do better audience segmentation. The part that is really missing, the valuable high quality data, are the first party data each company has in its marketing databases.
The tricky issue here is whatever company is going to be working on this first party data with their client needs to have the right security and the right privacy policies to make sure we respect the privacy of the end user. And I think this is the strength that Acxiom over the past 40 years has garnered.
Scott Howe: From a corporate direction perspective, we view Google as an incredible partnership opportunity as opposed to having any designs to develop something that looks like Google Analytics. Google already has a great product there.
The bigger issue for us is, yes, we have to be better at data visualization. The data is only ever as good as the utility it can provide to a marketer. To the extent we can help them visualize and build the proverbial knobs and dials over a database, that will make our products that much easier to use.
Phil is one of the very few guys in the world who has deep product and engineering experience, and also brings with that a practical sense of how to make that usable for people and then layer in a real frontier view of how data can be utilized in the future. It’s a really interesting skill set combination.
Could you carry that just a little further? Describe it from the point of view of an Acxiom client.
PHIL MUI: In the analytics space, if you think about seven or eight years ago, a lot of the tools, including even Urchin, these were tools that require technical expertise to even know how to manipulate. What made Google Analytics really unique in the Web analytics world is, all of a sudden here’s a tool that’s been developed that is aimed at a non-technical audience — which means, the actual decision makers in a marketing organization.
Where Google Analytics has done very well for web analytics is a good lesson for a lot of technology vendors. There are contextual differences here. One way to look at this general problem of technology and marketing is that in an organization there are probably 1 to 5 percent of technical people who know how to do advanced SQL queries for instance, and everyone else are simply data consumers, who in order to make a decision need insights and data.
Looking at it that way, in fact everyone should need to access certain marketing insights and data. What many tool vendors in the past have neglected is that in trying to make sure they are able to satisfy every last check mark in that RFP – they have neglected the fact that they want to make that product universally usable within an organization. The end point is not to provide additional features. The end point is to provide the insight to the decision maker who is able, in a very real time fashion, use it to make a business decision.
In the marketing database space– of course I’m very much a newbie here – my understanding is most vendors today are catering to a high level of sophistication, which is not necessarily everyone in a large organization. It would be fantastic if all of us in the industry could take a page of learning from how Google analytics have done in the past several years, and say, “Can we make our product significantly easier to use and more useful, not to the 1 to 5 percent of technical users, but to the 95 percent of the organization that requires data to make day to day decisions?”
SCOTT HOWE: What Salesforce.com has done, they’ve made CRM ubiquitous not only through the C-Level suite but throughout the organization. You use it for contract management. You use it for pipeline management. You use it as an input to your forecasting process. We think in the data space, a similar revolution is about to occur. Not only everyone in the C-level suite, but everyone in the organization, should be using data in some format to make better decisions. We’ve just got to give them that ability to do it.
If you succeed in making data accessible to the 95 percent of the organization that’s not technically oriented, what impact do you think that might have on your sales?
SCOTT HOWE: In our lifetimes there have been some real revolutions – whether it be Microsoft transforming the world of business efficiency through the mass commercialization of the PC and its software; or Facebook making staying in touch with your friends so much easier; or Apple making digesting music and media much easier.
There’s a similar opportunity in the data space for the world to utilize data more effectively – just to make better decisions wherever you are the organization. That to me is a staggering prize to unlock. I don’t know what the value of that is, but it’s as big a prize as we’ve seen in business.
What should we think of Acxiom as: a data company, an agency?
SCOTT HOWE: Certainly not an agency.
But you keep winning that award from AdAge.
SCOTT HOWE: Yeah, and it’s almost embarrassing because it sends a message to a bunch of partners like WPP and Publicis. They think we might be a competitor and we’re not. We need to make a transition to become SaaS – and a DaaS company if that’s a word.
It’s all about enterprise software for the collection, integration and utilization of data, along with the consulting layer that goes on top of that that helps our clients – not only our direct clients but their partners – understand how to use that data.
Ultimately we view our partner ecosystem as not just the direct clients we serve, but all the partners of those direct clients. Some will be agency partners, some will be email providers, some will be publishers. It’s a long list of folks that can utilize that data in an appropriately permission-enabled way to make better decisions.
Is the services layer growing? Shrinking?
SCOTT HOWE: Over time we’d like to see our software and data enablement layers grow faster. That service layer as a portion of our mix will decrease over time. Certainly that’s not the area we’ve been making big investments in recent months.
Phil, you’re moving from a young organization to a relatively mature one. How will the differences in the software development culture of the two places affect you?
PHIL MUI: Acxiom has 40-plus years bringing a very distinguished set of technologies and services to the industry. There are a lot of processes and good methodologies that have sustained Acxiom for so long. I’m looking forward to learning these best practices.
It is very hard for a young company, like Google, to have a comprehensive approach – in the enterprise space, making sure we have the right security and privacy well thought through. Over the past decade, it’s an area Google is becoming good at, and it’s an area that someone like me – coming from Google – can learn a lot at Acxiom.
In terms of things I can bring to the Acxiom culture, which could be constructive, it’s that young culture of agile development practices. Here at Google we have a weekly release. Now, for most enterprise software, you’ll be lucky if you have a quarterly release, if not a yearly release.
Would you both give a quick take on the exchange-traded media space?
PHIL MUI: The display, real-time bidding, DSP space for the past few years has been trying to bring in more targeted audience data in order to help the client be more efficient.
The majority of audience data people are using today are third party cookie data. Third party cookie data have a lot of problems. One is that cookies churn significantly. Secondly, it’s not very accurate. If you ask an agency or end user who has used this third party cookie data, they’ll tell you it’s a hit-and-miss thing whether this third party segmented cookie data really works.
There’s a recognition that first party data is increasingly important. I suspect in the next couple years there will be an increasing number of offerings coming out to look at this higher quality first party data, rather than the third-party data which is very prevalent these days.
SCOTT HOWE: There’s the old metaphor of the five blind men who are asked to touch an elephant and figure out what it is. If you recall the story, each one of them thinks it’s something very different because they touched the trunk or the hide or the foot of the elephant.
I look at this space. It’s an incredible success story within the fairly narrow siloes within which things have been built. The next challenge is you look at the whole elephant to understand it’s an elephant. So too you have to look beyond the narrow siloes to get maximum value out of the information . We’re entering an era where flexibility, connectivity, and data breadth become as important as niche targeting and predictive algorithms were over the last five years.
By Zach Rodgers
