Matt Shanahan, SVP of Strategy for Scout Analytics, a behavioral analytics platform for publishers.
AdExchanger.com: What problem is Scout Analytics looking to solve?
Scout Analytics helps publishers price, negotiate and deliver on ad campaigns by addressing three challenges: segmentation, accuracy, and prediction. A publisher that has deeper segmentation can create customizable packages and perform price discrimination of those packages. With more accuracy about reach and frequency, the quality of the publishers impression increase and allow for further pricing negotiation. Finally with prediction, a publisher has a better forecasting on the inventory of impressions during negotiations to provide confidence on performance to plan.
What is the challenge with cookies for marketers looking to count their users, let alone target them and getting them to register?
Cookies are highly precise but terribly inaccurate. A cookie is a small file on the computer that registers if this browser has accessed the site previously or not. The first challenge is that these files are routinely deleted by visitors which overstates reach of impressions and understates frequency. The second challenge is that cookie counts are a measurement of unique browsers, a proxy for visitors but not actual visitors. In a recent study published, Scout Analytics showed that actual unique browsers overstate actual unique visitors by 2-4X. In this case, the reach and frequency measurements on impressions have a high degree of error. Scout Analytics leverages a technology called device signatures to overcome the limitations of cookies and build a deeper profile of visitors, especially anonymous visitors.
Publishers are in the midst of transition to digital and in need of a new breed of tools for audience development. B2B has some advantages over B2C in terms of tackling the challenges of segmentation and prediction.
B2B publishing is by definition relies on advertising to niche audiences. In B2B, there is wealth of untapped online data to create deeper segmentation for use by publishers and advertisers. For example, anonymous B2B visitors have IP addresses to target based on geography and on the organization that owns the domain (i.e., industry specific or even company specific campaign). In addition to the rich segmentation collected in session data, external data sources can be easily integrated with visitor data to build deeper and deeper segmentation.
Another leverage point is the fact that B2B websites are linked directly to business processes which can be used to be more predictive. Mapping visitor behavior to common business cycles gives a publisher a lens on visitor activity. Is a visitor using the site for a one-off project or routine processes (e.g., daily, weekly, quarterly, or yearly)? Even topic affinity by industry provides predictive power to a publisher knowing how visitor demographics will change based on news or what is driving economic activity by industry.
What do you report out to the publisher? Any examples you can provide of actionable data?
Scout Analytics reports visitors and companies and their relative ranking in terms of visitor loyalty (i.e., likeliness to return). Detail visitor loyalty reports identify patterns such as days, time, location, and topics of visits (e.g., when and why is a visitor likely to return) and can be used to predict reach and frequency of impressions. Scout Analytics also reports what factors correlate to visitor loyalty such as topic, industry, location or other factors. Armed with this information, Scout Analytics provides target visitors to editorial, audience development, and ad operations for building and monetizing loyalty.
Do you provide datasets that can be used for ad targeting?
Yes, Scout Analytics can provide visitor level information to include segmentation as well as loyalty scores. In particular, the loyalty scores allow for serving offers according to the level of engagement of the visitor.
Given privacy concerns regarding online advertising, your company appears to be focused on overcoming it by getting users to agree to the publishers terms. Fair statement?
Building and monetizing an audience requires publishers take responsibility for establishing privacy terms between the audience, themselves, ad networks, and advertisers. In that regard, the publisher needs to appropriately inform all parties about the “rules” of engagement and ensure compliance. That means visitors need to agree to a publisher’s terms. Ultimately, the visitor has control in regards to online advertising by opting out (i.e., don’t use the site).
How does Scout Analytics revenue model work?
Scout Analytics is a software-as-a-service offering. The licensing is an annual subscription model. The pricing is based on 4 tiers for small, medium, large, and extra large sites.
How big is the company? Have you taken any funding? Do you anticipate a round in the future?
We currently have 18 staff and have taken funding from Ignition Partners, RRE, and OVP venture firms. Our current funding allows us to build and grow the business organically.
A year from now, what milestones would you like the company to have achieved?
Scout Analytics believes increased accuracy of campaign metrics are fundamental to improving advertising spend efficiency. We hope to establish the standard for online measurement accuracy. When combined with predictive analytics, we would like to see the efficiency of advertising spend increase 50%+. Our delivery on that goal will have doubled our customer base, made us profitable, and given us good growth options.
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