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Showing posts with label customer data management. Show all posts
Showing posts with label customer data management. Show all posts

Friday, 22 November 2013

Marketing Automation News from Dreamforce: B2B More Integrated, B2C Stays Separate

Posted on 08:35 by Unknown
I spent the early part of this week at Salesforce.com’s annual Dreamforce conference. Here are my observations.

The big news was for geeks. The main theme of the conference was Salesforce1, a new set of technologies that make it vastly easier to deliver and integrate mobile versions of Salesforce-based applications. It is apparently a major technical accomplishment and at least one of my technical friends was hugely impressed. But I can’t say I personally found it all that exciting. Perhaps we’ve reached the point where we expect technology to do pretty much everything, so the line between what's already available and what's new is only visible to experts.  Any way you slice it, focusing on platform technology is much less exciting than last year's vision of "social enterprise".

The bad news was for B2B marketing automation. Conference presentations confirmed that Pardot, the B2B marketing automation system that Salesforce acquired as part of its ExactTarget acquisition, has been separated from the rest of ExactTarget and made part of the Sales cloud. There, Pardot is described only as providing lead scoring and nurture programs, which ignores landing pages, behavior tracking, and other features that B2B marketing automation usually provides (and Pardot includes). In terms of infrastructure, Pardot will eventually work directly from the CRM data objects, rather than maintaining its own synchronized database. (Data outside the CRM structure, such as detailed Web behaviors, will remain separate.)

What this means is that Salesforce sees B2B marketing automation as just an appendage of sales automation.  This is pretty much the same constricted view of marketing automation that Salesforce management has held all along.  The logical consequence is to make lead scoring and nurture campaigns standard features within the Sales offering and discard Pardot as a separate product.  I should stress that no one at Salesforce said this was their plan, but it seems inevitable. If and when that does happen, only the most demanding companies will purchase a separate B2B marketing automation product.

To put a more optimistic spin on the same news: Salesforce will continue to let independent B2B marketing automation apps synch with Sales.  If Salesforce does merge Pardot features into its core Sales product, then marketers who have a more expansive view of B2B marketing automation functions (or who simply want a system of their own) will be forced to buy from someone else.

The interesting news was that B2C marketing automation remains separate. Salesforce’s list of business groups includes the Sales Cloud, Service Cloud, and ExactTarget Marketing Cloud. Did you notice that just one of these has its own brand? As this suggests, and conference presentations confirm, Salesforce has kept B2C marketing distinct from its Sales and Service businesses, most importantly at the data and platform levels. The ExactTarget Marketing Cloud does now include Salesforce’s previously-purchased social marketing components, Radian6 social monitoring and Social.com social advertising. It also includes the iGoDigital predictive personalization technology that came along with the ExactTarget acquisition.

Salesforce did announce some plans to integrate the Marketing cloud with Sales and Service, but they are pretty much arm’s length: Marketing can receive alerts about changes in Sales (and I assume Service) data, even though that data remains separate; Sales and Service can send emails through the ExactTarget engine; Sales and Service can receive content recommendations from the Marketing predictive modeling tool. As near as I can tell, this is the same type of API-level integration available with any third-party system. For what it’s worth, the ExactTarget Marketing Cloud APIs are also part of Salesforce1, but don’t confuse that with sharing the same underlying platform.They don't.

The good news is the B2C marketing vision. It’s not really surprising that Salesforce kept its B2C platform separate, since Salesforce's core technology isn’t engineered for the massive data volumes and analytical processing needed for B2C in general and consumer Web marketing in particular. Happily, this technical necessity is accompanied by what strikes me as a sound vision for customer management.  ExactTarget framed this around three goals: single view of the customer; managing the customer journey; and personalized content across all channels and devices. It described major features for each of these: a unified metadata layer to access (and optionally import) data from all sources; a “customer journey” engine to manage multi-step, branching flows; and predictive modeling to select the best offers and contents across email and Web messages.

This felt like a more coherent approach than Salesforce described for the Sales cloud, where external data and predictive modeling in particular were barely mentioned (or, more precisely, are still being left to App Exchange partners). The ExactTarget cloud still lacks tools to associate customer identities across email, phone, postal, social, and other systems, although there are plenty of partners to provide them. I didn’t get a close look at the details of the ExactTarget functions, which will really determine how well it competes with other customer management platforms. But the general approach makes sense.

News of the revolution may be exaggerated. Salesforce argued during the AppExchange Partner keynote that the AppExchange and Salesforce platform have created a “golden age of enterprise apps” by enabling small software developers to sell to big enterprises. One part of the argument is that the platform itself lets small vendors break through the credibility and scalability barriers that have historically protected large enterprise software vendors. The other is that end-users can purchase and deploy apps without involving the traditional gatekeepers in enterprise IT departments. A corollary to this is that end-users have different priorities than IT buyers – in particular, end users care more about ease of use – so successful software will be different.

Of course, this is exactly what the AppExchange partners wanted to hear and exactly the strategy behind Salesforce’s platform approach in the first place. But that doesn’t necessarily make it untrue: and, if correct, it would indeed be a revolution in the enterprise software industry.

But some revolutions are bigger than others.  Even in an app-based world, individual users won't be making personal decisions about how to run core business processes.  Rather, systems will be chosen at the department level because companies can more or less safely assume that whatever the department chooses will integrate smoothly with the corporate backbone. That's certainly a change but bear in mind that departmental buyers will have the same preference as corporate IT groups for working with the smallest possible number of vendors. This means there will still be the familiar tendency for individual vendors to add more functions over time. So industry dynamics may change less than you’d expect.
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Posted in app exchange, customer data management, dreamforce, exacttarget, marketing automation, marketing software trends, pardot, predictive modeling, salesforce.com | No comments

Thursday, 19 September 2013

New Study: Three Types of Customer Data Platform Address Cross-Channel Marketing Needs

Posted on 17:57 by Unknown
My detailed study of Customer Data Platforms should be released next week. Now that the information is assembled, I can at last pull back and get a good overview of what I’ve found.

Perhaps the most interesting discovery has been that the CDP vendors cluster into three main groups.

• B2B data enhancement. These build a large reference database of companies and employees, which they match against records imported from their clients. They generally return corrected and enhanced data and lead scores based on models built from the client’s customer files. Their reference databases are built from multiple public, commercial, and proprietary sources, and are assembled using sophisticated matching engines. Most also perform their own scans of Web sites and social networks to extract sales-relevant information such as technology use and changes that suggest buying opportunities. These vendors vary considerably in the data they return, ranging from lead scores only to recommended marketing treatments to full customer profiles. Some also provide prospect lists of companies that are not already in the client’s own database. CDP vendors in this group include Infer, Lattice Engines, Mintigo, and ReachForce.

These systems compete with non-CDP products which also add or enhance prospect records but do not maintain a database with their clients’ customers. These include Web scanning systems such as InsideView, LeadSpace, and SalesLoft, and general data compilers including NetProspex, Demandbase, Data.com, ZoomInfo, and OneSource. The predictive modeling features also compete to some degree with end-user-oriented marketing analytics and modeling software such as Birst, GoodData, Cloud9 Analytics, AutoBox, and Predixion Software. Data cleansing competitors include services from firms such as D&B, as well as data management software for technical users such as Informatica, Experian QAS, and FullContact.

• Campaigns. These systems build a multi-source marketing database from the client’s own data and either recommend marketing treatments to execution systems or execute marketing campaigns directly. These are primarily used for consumer marketing although they also have B2B clients. Most have sophisticated matching capabilities. This group includes Silverpop with its Universal Behavior feature, NICE’s Causata, AgilOne, and RedPoint.

This group competes with conventional consumer marketing automation products, which provide similar campaign management abilities but lack the CDPs' database flexibility, database management, and customer matching features.

• Audience management. These systems build a database of customers and their responses to online display advertisements. They then build models that predict the customers’ probability of responding to future advertisements and provide recommendations for how much to bid and which content to display. These systems perform the same basic functions as standard online audience management systems (Data Management Platforms, or DMPs) and provide the same very quick responses needed for real time bidding (usually under 100 milliseconds). The major difference is that they also recommend messages in other channels, such as Web site personalization or email campaigns. Like DMPs, they work primarily at the Web cookie level, can link cookies known to relate to the same customer, and can be linked to actual customer names and addresses in external systems. This group includes IgnitionOne, [x+1], and Knotice.

This group overlaps with recommendation and ad targeting engines and DMP systems. Those products provide similar functions but do not track identified individuals and are often limited to single channel executions.

Given that each group addresses a different business need, you might wonder why I think they should all be lumped together under the CDP label. Quite simply, it’s because they are all addressing a portion of the same larger problem, which is how marketers can get a complete view of their customers and use that view to coordinate treatments across channels. What marketers truly need is a combination of the features from each group: data enhancement from external sources, for consumers as well as B2B; sophisticated customer matching and treatment selection; and integration of online advertising audiences with traditional customer databases. Each of these systems has the potential to grow into a complete solution, and the normal dynamics of software industry growth will push them towards pursuing that potential. So I expect the categories to overlap increasingly over the next few years and eventually merge into complete Customer Data Platforms as I envision them.

Incidentally and tangentially related: I'll be giving a Webinar with ReachForce on October 2 on Data Quality for Hipsters, a name that started as a joke but does make the point that data quality is essential for cutting-edge marketing.  YOLO, so you might as well attend.  I'm already working on the mustache.



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Posted in big data, customer data management, customer data platforms, customer data warehouse, customer information, data quality, dmp, enterprise marketing management, marketing database | No comments

Thursday, 23 May 2013

Customer Data Platforms: My New Whitepaper Explains the Excitement

Posted on 16:16 by Unknown
You may have noticed that I've been uncharacteristically aggressive in promoting the Customer Data Platform concept.  Sorry, but I just can't help it: a new system category is even more rare than a new B2C marketing automation system (which, as yesterday's post pointed out, is much rarer than a new beetle).  More important, I think the category itself is a very important development that could really help marketers solve some big problems.  So it's worth several shoves to get the ball rolling.

Along those lines, I am embarrassingly excited to report my formal whitepaper explaining the CDP in depth has just been published.  It was sponsored by ReachForce but they had no influence on the actual content. (In fact, they probably would have preferred something a bit more on-message for their own marketing, so let me thank them for their indulgence.)  You can download it here.  Comments are welcome!


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Posted in customer data integration, customer data management, customer data platform, marketing automation, marketing systems, predictive analytics | No comments
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