0 Adometry Combines Attribution with Optimization

So…my last two posts on attribution systems (MMA and VisualIQ ) were among the least popular ever, right down there with Marketing Lessons from Chernobyl (which, let’s face it, was in pretty poor taste). But vox populi isn’t always vox Dei, eh? I think it’s an important topic, so here we go again.

The lucky recipient of that less-than-stirring introduction is Adometry, which in no way deserves any disrespect. From humble beginnings in click fraud prevention, they have grown in recent years to be one of the leaders in algorithmic response attribution. Their latest expansion moves them beyond digital channels to offline media including direct mail, television, and print. They have also moved from attributing past results to using predictive models to optimize current and future campaigns. Impressive.

The core of Adometry’s attribution methodology is to compile the sequence of marketing messages seen by each individual, and then compare results of individuals whose sequence differs by only one message. Any difference in results is then attributed to that message. This is conceptually simple, but requires clever treatments to handle low volumes for specific sequences and to isolate the impact of attributes such as placement, time slot, creative, and list segment. Adometry also lets users model against multiple events in the customer life cycle, such as sign-ups, first purchase, and repeat purchase. It calls these all conversions, which I personally found a bit confusing but suppose would quickly get used to.

The system also classifies each conversion as attributable, multi-touch, and multi-channel, depending on whether it was linked to at least one message (attributable), to multiple messages (multi-touch) and to messages in multiple channels (multi-channel). For each category, it shows the conversion count and revenue: so, for example, you see the number and revenue for multi-touch repeat purchases. That’s a lot of information to digest, but does give a great deal of insight into the effect of different promotions and channels on different parts of the business. This encourages marketers to look beyond any single measure, such as cost per order, that tells only a small part of the business story.

The system’s optimization process begins with the attribution analysis, but then adds auto-generated predictive models to estimate the impact of future ad plans, including interactions across channels. Users can enter scenarios with budgets for multiple channels and campaigns, and then apply other constraints such as limits on the change in spending per channel. They also define output measures for the system to optimize against: like other optimization systems, Adometry can only optimize against a single measure, but this can be a composite of several items. For each scenario, the system will determine the optimal budget allocation and show the expected results across each output measure. Users can modify the recommended plan and have the system re-forecast the results. The final plan can be output to a spreadsheet for further editing. Adometry can also be connected directly to ad buying platforms, including systems for real time bidding on individual impressions.   The company says optimization typically yields a 20% to 40% improvement in ad-to-sales ratios.

The database of marketing messages per individual can be used for other types of analysis. These include reach and frequency reports, which show the number of individuals reached in total, reached in each channel, and reached exclusively for each channel. The reports count impressions as well as individuals; show how many people were reached in each combination of channels; show the number of people with each number of impressions (one, two, three, etc.); and show the current member count in each funnel stage.

Adometry’s data comes primarily from tags embedded in advertisements, emails, and other online messages, which drop cookies to identify who sees which message. The system can also draw data from Web server logs or third party tags. Adometry can further enrich its database by appending external information about individuals, using both online and offline sources. This lets it profile the audiences associated with different events, channels, campaigns, and other attributes. Optimization models can use data that can’t be tied to specific individuals, such as weather, economic conditions,  and mass media like television and print. The system can also verify which ads were actually seen by individuals, providing more precise inputs to the attribution calculations.

Pricing for Adometry is based on the number of channels and volume of data. It starts around $100,000 per year for the smallest clients with enough volume to use the system effectively (about 30 to 50 million impressions per month). Currently, more than 50 companies use Adometry’s attribution services.

0 ReachForce Buys SetLogik: One-Stop-Shopping for B2B Marketing Data Plus Database

B2B marketing data vendor ReachForce today announced its purchase  of SetLogik, which provides technology to build cloud-based marketing databases and do predictive modeling against them. (See my post from last October for more on SetLogik.)

There’s an obvious peanut butter-meets-jelly type of logic to this match. Reachforce’s core business is assembling data on marketing prospects, which it then sells for as many uses as possible: appending to Web leads, enhancing existing databases, and buying as lists. The SetLogik acquisition takes this a step further by letting them build databases to hold their data, thereby expanding the market beyond people with a database already in place. Conversely, having a readily-available data source encourages marketers to build their own database. SetLogik’s predictive modeling features make it even easier for marketers to get a return on their investment once the database is in place. Everybody wins!

The two products will be combined in what ReachForce calls the “Connected Marketing Data Hub”. The name is frightfully generic, but the key points are:

• cloud-based system, making it easy to deploy
• comprehensive customer view including data from marketing automation, CRM, transaction systems, and ReachForce’s own sources
• continuously updated and cleansed
• connectors available for Salesforce.com, Eloqua, and Marketo  

In other words, the ReachForce solution supplements rather than replaces your marketing automation or CRM database. As I wrote in my earlier SetLogik review, one particularly attractive result is the ability to match sales revenues with marketing leads, always a challenge in measuring the value of marketing programs.

ReachForce has just begun to offer the combined system, which is currently deployed at one pilot client. Pricing is based on data volume, whether the client wants a one-time append or continuous cleaning, and on the data sources included. Minimum is $625 per month for continuous cleaning on 50,000 records.

0 Marketo Files for IPO: Will High Growth Outweigh High Losses?

Marketo made good today on its promise to file for an initial public offering (IPO). Congratulations to them for reaching this step. It’s a major accomplishment.

The S-1 registration statement gives considerable new information about Marketo’s business. Revenue for 2012 is reported at $58.4 million, an impressive 80% growth rate vs. 2011 although not quite the doubling that the company had forecast earlier.

More significant, the company continues to have huge losses – it lost $34.4 million in 2012, or 59% of revenue. By comparison, Eloqua lost just 7% of revenue in the year before its IPO, and even Salesforce.com, the benchmark for all Software as a Service (Saas) start-ups, lost just 20% of revenue in its final year as a private company.

 A loss that big is pretty scary. Part is due to heavy spending on sales and marketing – 65% of revenue – but that’s not the whole story: Salesforce.com had also spent 65% on marketing before its IPO (although Eloqua spent just 40%).

The difference is that cost of revenue (costs of delivering service to clients, including subscription, support, professional services, and other) was 42% for Marketo, vs. 20% for Salesforce.com and 32% for Eloqua. That figure hasn’t changed in recent years, suggesting economies of scale have yet to appear. A high cost of revenue makes it hard for a company to become profitable even as it grows, since much of the new revenue is spent on the new customers. SaaS economics aren’t supposed to work that way.

Marketo’s other operating costs (research and development and general and administrative) are also high – 52% of revenue, compared with 35% for Salesforce.com and 33% for Eloqua. That percentage has also been pretty much stable for the past three years – again suggesting that expected scale economies haven’t appeared yet.

Another way to look at it is this: Marketo would earn just 6% profit even if its sales and marketing costs were zero. So its losses aren’t simply due to high investment in new customers.  The comparable figures for Eloqua and Salesforce were 39% and 45%, respecitvely.

The S-1 also reports the company had 339 employees as of December 2012. Of course, the average for the year was much lower but, ignoring that, this still yields a perfectly respectable $172,000 revenue per employee. But it also means expenses are $273,000 per employee – much higher than the $200,000 rule of thumb. I know everyone at Marketo works incredibly hard, but something is clearly out of line in their cost structure.

Perhaps stock investors will look only at Marketo’s growth rate. There is certainly an argument that the company will eventually become profitable as it spreads its fixed costs over more revenue.   On the other hand, as I argued recently in DemandGen Report,  it may not be possible for any large marketing automation firm to thrive as an independent.  If that's correct, then Marketo's growth will never happen and the investors' only hope will be a buy-out by a larger firm.  Let’s hope the stock market sees hope somewhere in all this: otherwise, Marketo stock will be much harder to sell than its software.

0 InfusionCon 2013: InfusionSoft Keeps Its Focus on Helping Entrepreneurs

I spent part of last week at Infusionsoft’s annual conference, InfusionCon, drinking the Kool-Aid and soaking up the Arizona sun.


Pleasant as the 80 degree temperatures were to a refugee from the still-wintry Northeast, the real warmth at the conference came from 2,300 attendees bubbling with enthusiasm for their entrepreneurial adventures and how Infusionsoft supports them. Keynote speaker Jay Baer captured the mood perfectly when he went “all Oprah” on the crowd by promising them each a free Camaro. (Either he was joking or I registered incorrectly.) The group was indeed drenched in Oprah-style self-empowerment.

As you’ve probably guessed, this isn’t my native habitat. Even though Raab Associates itself is a small business and runs in part on an Infusionsoft-like system (OfficeAutoPilot), I’m a professional manager by training and most of my clients are mid-size and big businesses. What really matters, though, is that Infusionsoft itself remains committed to its small business customers, despite growing to nearly 400 people and $40 million revenue. This consistency is no accident: Infusionsoft managers are quite vocal on their very conscious efforts to build a culture that is committed to helping entrepreneurs and is itself entrepreneurial. It’s a tall order, but there’s some serious missionary zeal at every level, so they might just succeed.

In any event, I did manage to spend most of the conference in my own comfort zone of analyzing Infusionsoft’s business. A long conversation with Chief Marketing Officer Gregg Head provided some interesting tidbits, including:

- the company’s customers fall into three main groups, each roughly one third of the total.  hese are: Internet-enabled business coaches and experts, who are selling books, videos and other products in addition to their personal time; local service providers, such as dentists, home services, and fitness centers; and businesses selling to other small businesses.

- most clients want either to increase sales or free up the owner's time. The latter goal – taking back your life from an all-consuming business – seemed to resonate more than anything with the attendees. Reducing costs is a lower priority.

- Measuring return on investment isn’t much of an issue. Small businesses can see changes in revenue or free time immediately.  Detailed analysis isn't needed.

- Some companies are too small even for Infusionsoft. A client must have a stable revenue base to expand, or be successful enough that the owner is looking for some free time. The average Infusionsoft client has been in business for five years, which means that nearly all were in business for at least several years before purchasing the system.

- Facebook is by far the most important online channel for Infusionsoft customers, in many cases replacing Web sites as the primary online presence. Search engine marketing and blogs are much less important. The primary sources of new customers are still offline: referrals, partners, events, and direct mail. (Incidentally, trendsters, direct mail in general and post cards in particular are hot. But that might be old news. I did receive a message about personalized pizzas today, but am pretty sure it was an April Fools joke.)

And what of Infusionsoft itself? The company did announce its next release at InfusionCon, although by its own admission the changes were incremental enhancements in usability rather than major expansions in function. The main items were more efficient scheduling of personal tasks, a simple way to prepare quotes, and branding templates that automatically deploy style changes across all types of content. Campaigns can also now easily include GroSocial Facebook campaigns (GroSocial being a social marketing firm acquired by Infusionsoft in January.) Modest as these changes are, the company says its users wanted them more than new acquisition channels.

Infusionsoft also announced several non-technical initiatives, again with the goal of making users more productive. These included a set of prebuilt campaigns. including actual content; on-demand training videos integrated with the product, and accelerated expansion of sales and service partner networks. The onboarding process has also been revamped to deliver results in 30 days rather than 60, the main change being that Infusionsoft staff now does more of the actual setup for new clients and spends less time on a conceptual success map.

All these changes confirm what was already obvious: that Infusionsoft’s entrepreneurial customers are a separate breed from the professional marketers who use traditional marketing automation systems. The functional differences between the two sets of systems may be hard to spot, but there’s no mistaking the difference in the services and attitudes that surround them.

0 How to Get the Most from Social and Behavioral Data: Webinar, March 19

Raab Associates has been gradually relocating from New York to Pennsylvania over the past two weeks. I won’t subject you to a post like “what B2B marketers can learn from moving companies”, which is one of my least favorite ploys for repackaging old advice in a “fun” format. In fact, I only mention it to explain why I haven’t been writing with my usual frequency and why this post is relatively brief.

Still, I did want to let you know that I’ll be giving a Webinar next Tuesday, March 19 at 2 p.m. Eastern on “Making the Most of Social and Behavioral Data for B2B Marketing”. It’s sponsored by Mintigo, a hard-to-classify vendor with technology to scan the Web for prospects and predict their interests. You can register here.

The chaos of moving has slowed down my slide preparations, which are made even harder by the fact that our 100-year-old house has such uneven floors that my chair keeps rolling away frrrrom mmmy desssssk. But I did finish my research before they packed up our computers, so the content itself will be solid. Without giving away all the goodies, some of the more interesting things we’ll cover include:

- where social and behavioral data are used in the marketing process. This actually matters quite a bit: there are some things that social and behavioral sources can provide, and others they can’t. You have to be sure you’re using them correctly and supplementing with other sources where appropriate.

- what to do once you capture the data. Traditional marketing data was pretty easy to manage because there wasn’t that much of it.  With social and behavioral, you’re surfing a flood. We’ll talk about how to keep your head above water.

- how to deal with the ephemeral nature of much social and behavioral data: without belaboring the flood analogy, conditions change rapidly and marketers must react quickly. We'll discuss what this means and how to do it.

- which data elements are available from different sources.  It isn’t news that each social network works differently, but it’s still eye-opening to see just how distinct they are. We'll talk about which network is best for different purposes.

- what all this looks like from a sales person’s viewpoint. Most marketers will try to swim in this data despite the rough surf. Sales people are more likely to leave the water and have a hot dog. We’ll talk about ways to keep them immersed.

I’m more curious than anyone to see my final slides, but have no doubt that the session will be useful and interesting. It’s an important topic: join me if you can.