Wednesday, February 25, 2015

Will New Marketing Automation Tools Let Sales Climb Back Up The Funnel?

Trends are signposts to the future: they point to where we’re headed. But the signposts are unreliable because trends are often interrupted – the classic example being the “Great Horse Manure Crisis of 1894”, when experts predicted that major cities would soon be buried beneath horse droppings. I’m beginning to suspect the much-cited trend of marketing playing a larger role deeper into the sales funnel has reached a similar peak. If the pendulum is really swinging the other way, then sales people will be taking a more active role earlier in the buying process.

This particular thought emerged quite unexpectedly during a vendor briefing yesterday. The talk had turned to the industry in general and I was ticking through my usual list of trends – external data, predictive modeling, sales enablement, advanced attribution, adtech and martech integration, local/partner marketing systems, all-in-one systems, content creation support, and of course customer data platforms. But I also had in mind another system I had just seen, MDCDOT, which gives marketing automation functions to sales people. For some reason, I suddenly saw a connection of this to external data: if vendors like NetProspex and InsideView could provide sales people with prospects and vendors like MDC provide tools to nurture those prospects, then sales people really don’t need marketing to do either of those things. Sales could then push marketing back to its traditional narrow role of generating promotional materials and doing research. That's pendulum swinging with a vengeance.

Once an idea like that pops up, supporting arguments quickly fall into place.  Integration of advertising with marketing technology potentially gives sales people another route for generating their own prospects. Advanced data enhancement and lead scoring make it easier for sales people to automate lead nurture processes without becoming marketing automation experts. All-in-one systems and customer data platforms both unify marketing and CRM technologies, making it easier to shift boundaries between marketing and sales responsibilities.  Those shifts could be permanent or vary dynamically based on fluctuations in needs, resources, and individual interests. Sales enablement tools like Velocify and Clari help salespeople pick the right treatment for each prospect, which can include sending them to automated campaigns.

In short, the conditions may be ripe for a counter-revolution: a sort of Terminator 2-style conversion where some machines defend the humans instead of trying to replace them. It even dawns on me that having marketers restrict their focus to content creation has some advantages, given how much more content is needed these days.

Let me be clear: this is a shiny new idea which could quickly lose its luster. It only applies in B2B and considered-purchase B2C relationships where actual salespeople are involved in the buying process. And it may be that most salespeople are happy to let marketers handle the lead generation and nurturing, which they never enjoyed in the first place. Or perhaps corporate management will decide it’s more effective and safer for marketing to handle those tasks, regardless of what sales people want.

On the other hand, sales departments are usually much larger, more powerful, and better funded than marketing departments, so it could be in the marketing automation vendors’ interest to serve sales people directly. This leads to the long-expected assimilation of marketing automation into CRM, a trend that has never quite happened but might finally take place.

Or maybe the future is really about machines selling to other machines, and the whole distinction between sales and marketing will no longer matter. Only time will tell. In the meantime, bear in mind that you never know whether a signpost is correct until you’ve passed it.*
*I don’t know what that means, either, but it sounds pretty deep, don’t you think? I can definitely see the motivational poster.

Thursday, February 19, 2015

Ensighten Transforms Web Tags into Rich Customer Data

Looking back once more at last month’s post on the future of marketing data, you may recall that I briefly mentioned the intriguing rise of Web tag management systems as platforms to integrate customer data. Tealium highlighted the topic on Tuesday with $30.7 million in new funding, bringing the total to $77.9 million to support its stated mission of “capturing and serving up real-time, 360-degree customer insight to all of their [customers’] enterprise applications.” Sounds like a Customer Data Platform to me.

But I'll get back to Tealium some other time.  Today I'm writing about Ensighten, another major player in the tag management space, and one that is also pursuing a much grander vision: to be an “open marketing platform” that lets clients build a “custom marketing cloud”.

If origin stories count, and I think they do, then it’s worth noting that Ensighten’s started in 2009 as a digital analytics agency. Frustrated by the limits that traditional tagging methods placed on clients’ ability to move quickly, the firm developed an engine to generate custom sets of tags for each Web site visitor. This differs from the more common approach of serving one container that holds all possible tags.  (The problem both solutions address is that many Web pages contain a large number of tags from different systems; tag managers consolidate those tags so load more efficiently and are easier to control.) Ensighten’s method meant that only the tags that would actually fire for a particular visitor were loaded, while a container serves all tags and lets the Web page figure out which to fire. Ensighten studies have found it reduces page load time by 40% and tag deployment time by 75%.

Whatever the relative merits of Ensighten’s approach to tag management, the company’s focus today is on the data itself.  In particular, Ensighten wants to ensure data from the tags is available for the client’s own use. This regains control that is lost when partners place their own tags on company Web pages and don’t necessarily share the resulting information.

As I’m sure you see coming, Ensighten’s next step is to assemble the tag data into detailed individual profiles for personalization, testing, attribution, and other purposes. Ensighten added these capabilites a year ago, just after taking a $40 million investment (bringing its own total to $55.5 million if you're keeping score). These features go beyond Web page tags to capture data from mobile apps, from ad pixels served on external Web sites, and from other systems via batch data imports. They also include processes to merge profiles using customer IDs, cross-reference tables for IDs from different systems, probabilistic matching of shared data elements, correlated behaviors, and links between individuals and devices.  This kind of identity association is arguably the hardest part of building an effective customer database and many systems don't do it.

Ensighten can deliver rule-driven personalized messages along with the custom page tags. It also provides services including Web site performance monitoring and privacy management and will apply machine learning to personalization and recommendations later this year.  But such applications are peripheral to the company’s long-term strategy of letting external systems use the data for their own purposes.  This is what puts the  “open” in “open marketing platform” and the “custom” in “custom marketing cloud”.

This approach means the company’s real competitors are other marketing suites and customer data management systems. Since last year’s funding, Ensighten has supported its strategy with acquisitions of tag management competitor TagMan in March 2014 and cloud analytics and predictive marketing vendor Anametrix in October 2014.  The TagMan deal put Ensighten's foot inside many new corporate doors, while Anametrix provided advanced technology for customer database management and analytics.

So far, it all seems to be working. Ensighten reported 150% revenue growth last year and says it now has “a few hundred” global clients, mostly very large enterprises. Pricing is based on volume, which could be Web traffic or audience size depending on the situation. The company doesn't release details but this is enteprise software: you can safely assume it’s not cheap.

I’ll end where I started: what Ensighten (and Tealium and others) are doing is remarkably clever: take a mundane service (tag management) that places them in a strategic position (touching all digital interactions) and use it to build a strategic service. Their starting point gives them a shorter path to building a company’s primary customer database than applications like lead scoring or customer success management, which must create new data flows before they can build the database they need to support their service.  The tag management vendors' position also lets them give equal access to all applications without worrying about competition with their own application services. And, from a purely practical stand point, it also gives them an initial relationship with many potential clients. This advantage alone is probably why Ensighten has so many more clients than the “pure play” CDP vendors Aginity or NGData I wrote about earlier this week.

Of course, the tag managers' success is not guaranteed. Building an integrated, persistent customer database is quite different from managing Web tags.  But it's always a good thing when marketers have more options.  Companies looking for help in building their core customer database should definitely take a look in the tag managers’ direction.

Tuesday, February 17, 2015

NGData Gives Enterprise Marketers a Customer Data Platform of Their Own

If you read my recent post on Customer Data Platforms Revisited very, very closely, you might have noticed it listed a category of data vendors who “store unified profiles and expose to other systems”, which is pretty much the core definition of a Customer Data Platform. You would also have noticed that category had only two members, Aginity and NGData. I reviewed Agnity back in November 2013 and when I spoke with them more recently, found they were still doing pretty much the same thing and growing nicely. But, until today, I’ve never discussed NGData.

I wish I could come up with a really cool reason for that, but it’s only because NGData just recently came to my attention. The company itself has been serving clients in late 2012. As my classification suggests, they are in the business of assembling client data from multiple systems, using it to build detailed customer profiles, and making the results available to execution systems like campaign management, call centers, Web sites, and mobile apps.

The technology involved is Hadoop as the primary data store and HBase to expose the profiles to external systems. Data is unified mostly with customer IDs supplied by the source systems, although NGData can also build cross reference tables to associate related IDs and do some probabilistic matching to link related devices. The profiles include both raw data and calculated metrics such as trends, exceptions, signals, affinities, predictions of fraud risk, churn likelihood, and next product to buy.  The predictions can be based on conventional predictive methods like regression or on integrated machine learning. Often the company is able to use regression models that the client has built already for other data sources. The base version of the company’s system, called Lily Enterprise, has about 700 such metrics, and clients can add their own. (There’s also an open source version of Lily, which has only the data management components of Lily Enterprise.)  External systems access profiles via SQL queries against HBase, API calls, or file transfers.

This may all sound pretty straightforward and should be familiar to readers of this blog. But out there is the real world, most companies are still struggling with the challenges of assembling customer data and making it accessible.  Those firms will find this is pretty novel stuff. NGData stresses its ability to easily add new data sources and to retain huge amounts of detail, something it inherits from Hadoop. Complex metrics like exceptions and trends are also relatively unusual.  They make it much easier for execution systems to act intelligently, since the hard work of surfacing opportunities and selecting responses is largely done in advance.  Predefining those metrics as part of the base system speeds initial deployment.   One proof point: NGData says clients can typically start running programs based on its system in four to five months, and sometimes as quickly as three months. Conventional data warehouse projects usually take more than one year and many are never delivered.*

NGData stresses that marketers get better results when they can look at all the data associated with each individual, rather than treating people as members of broad segments. Again, no reader of this blog will disagree.  But I did still like their example of using behaviors to identify people who are likely to call customer support with a particular problem, and then preempting those calls with personalized messages about how to solve the problem. Everybody wins: the customer appreciates the proactive service, and company fields fewer phone calls. The underlying point, which NGData stresses often, is that they're going beyond insight to producing an actionable result.

NGData also highlights the value of responding to customer behaviors in real time or near real time.  It can do this because it immediately updates its metrics in Hbase whenever it receives new information. Still is more old news, but conventional solutions often update their scores and recommendations nightly or even less often. To be fair, NGData can only update in real time if the source systems are providing immediate updates – which often isn't the case.  The vendor does have its own Web tags to capture real time information about Web visits, which lets it use in-session behavior to drive product and page recommendations.

The one thing you may not expect about Lily is that it’s old-style on-premise software, not software-as-a-service. That’s mostly because current clients are big companies in financial services, telecommunications, and media, industries that have been reluctant to let precious company data outside their walls (although plenty of hackers still manage to get it, he added snarkily). It’s also not clear how much SaaS would benefit NGData, since each client’s data store would remain separate in any case and the software needs to be installed on relatively few desktops. For what it's worth, Aginity is also on-premise and also serves primarily enterprise clients. 

I suspect it's no coincidence that the two "pure" Customer Data Platform vendors both focus on enterprises.  Smaller firms need to justify a CDP by combining it with a specific application, but big companies can afford a separate CDP project that they'll later tie to separate execution systems.  Perhaps this will change as CDPs get cheaper, the model is better understood, and integration with execution systems becomes easier.

NGData has about 25 current paying clients in Europe and the U.S. Pricing is based on volume of data and/or number of customers. Total cost for software and services starts around $150,000 to $200,000 and can go much higher. As I said, this is enterprise software.

*This is one of those things that “everybody knows” but few cab document. Here’s one paper that says data warehouses “usually” take 12 to 36 months, cost $1 to $1.5 million, and have a 70% failure rate. It’s not clear where the author got his data but it all sounds about right.

Thursday, February 05, 2015

VEST Report: Latest Trends in Marketing Automation, and Where's My Hoverboard?

I just finished the latest release of the B2B Marketing Automation Vendor Selection Tool, a.k.a. VEST Report. The new version includes a big technical change: instead of the interactive Flash document that was very cool but people often had trouble running, it’s now a combination of PDF for the core document and Excel spreadsheet for the detailed vendor scores. That’s a technical step backwards but will actually make it easier for buyers to access the detailed vendor information, and in particular to screen for vendors with particular capabilities. Less is more, I suppose. The good news is that this format lets me expand beyond 25 vendors, which was the maximum the old system allowed before running out of memory.

Of course, none of this is your concern, Dear Reader. What’s you'll find more interesting is that the VEST provides an opportunity to see new patterns emerging in the industry. Usually I do this by taking a close look at which features have become more common since the last report. But this time there were a few more obvious changes that stood out. Here’s what struck me.

- more micro-business vendors. All six of the vendors new to this report sell primarily to small businesses, and most are “all-in-one” systems that combine marketing automation with integrated CRM. They join another six vendors from previous editions who also serve this market. I'm also aware of several other vendors, not yet in the VEST, who also compete for this business. Many of these firms are new while others have been around for a few years but just hit my radar. What this says to me is that the all-in-one segment is more crowded and more mature than it has seemed. Of course, there’s still a huge opportunity – hundreds of thousands if not millions of potential clients have yet to buy their first system. But anyone planning to enter this business had better realize they will be fighting for new customers.*

- agency relationships. It seems that just about every vendor in the VEST now touts special features to support marketing agencies that resell the system to their clients or operate the system on the clients’ behalf. This isn’t exactly new but what once seemed like a niche strategy now looks more like a standard approach. It’s always been obvious that agencies were a sensible channel for marketing automation vendors to pursue, but I’m beginning to wonder whether agencies might turn out to be the primary channel for such systems, excepting only direct sales to large enterprises. If this happens, the reason will be that agencies provide the missing skills that have prevented so many companies from taking full advantage of marketing automation systems by themselves. Vendors have been knocking themselves out for the past five years trying to educate marketers to run their systems.  Perhaps having agencies run them is the real solution instead.

- social data. Maybe my biggest surprise was finding that many if not most vendors have now added features to automatically look up new contacts in social networks and add that data to their marketing automation or CRM profile. This seemed like magic three years ago when I first saw John Ferrara's Nimble do it; but now it’s commonplace. In fact, any vendor that hasn’t developed their own technology can just integrate FullContact to do it for them. So the competitive advantage is now precisely zero. (Okay, not zero: some companies surely do it better than others.  But that’s a much weaker selling point than being one of the few firms to do it at all.)

- ad tech integration. This one isn’t so common yet, although Oracle Eloqua, Marketo, HubSpot and some others have announced some ad retargeting partnerships. Google Adwords integration and advertising through Facebook, Twitter, and LinkedIn audiences are more widely available but I don’t include them here. But despite the slow growth, there’s no question that serious integration between Web display ads and marketing automation programs will become much more widely available. What I won't do is predict how quickly that will happen. But I’ll certainly add it to the list of VEST questions so I can track it more closely in the future.

- dogs that didn’t bark. That’s a Sherlock Holmes reference, not an insult to technologies that haven’t been as widely adopted as the industry seemed to expect. Okay, maybe it’s a bit of both. In any event, I didn’t commute to work today on my hoverboard, and you probably didn’t sit down to do advanced mobile marketing, predictive modeling or revenue analytics in your marketing automation system. Those three – mobile, predictive, and revenue analytics – are all technologies that should take off, but so far are not deeply integrated with most marketing automation platforms. Maybe mobile has become so ubiquitous that I don’t even notice it, but, so near as I can tell, few vendors have done more than make it easier to create emails and Web pages that look good on mobile devices. Surely mobile can do more than that. Predictive analytics are growing quickly but so far are still done by specialized vendors rather than built into the marketing automation platform. (Yes, there are a few exceptions like the machine learning features of dbSignals and RedPoint. But they’re exceptions.) Revenue analytics is only discussed by a couple of companies; although important, it doesn’t seem to have captured the industry’s imagination. I haven’t given up hope for any of these, but no longer expect them to quickly become part of the mainstream.

So those are my impressions while the VEST updates are fresh in mind. The report is well worth buying if you want do to your own industry analysis, or (its primary purpose) are searching for a new system. As I say, the new format does make finding vendors with specific features much easier. You can find more information or place an order at Let me know what you think.

*In fact, the micro-business segment is even more complicated than I’ve suggested. The real competitors are companies like ConstantContact who are providing a broad range of services, such as local advertising, that extend well beyond marketing automation and CRM. There are also many vendors with specialized services for vertical markets such as plumbers and funeral homes. Come to think of it, I recently noticed that one of my many plumbers (don’t ask) uses a system developed by a funeral home website firm. If there’s a logical connection between those businesses, I don’t want to know about it.