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Multiple Applications, Yet One Marketing and Sales System

September 04, 2014 | By Jay Famico

Although every piece of sales and marketing technology addresses specific user needs, each contains data on the same group of customers, prospects, influencers and partners. Therefore, these applications must be connected within the full spectrum of b-to-b sales and marketing technologies.

How do b-to-b marketers drive demand? How do sales reps manage prospect and client relationships? Using technology. While marketing must define campaigns, programs and tactics, and sales must understand a client’s needs and engage the client with these in mind, technology is how they do it.

Technology ModelFor instance, marketing uses marketing analytics, Web analytics, business intelligence applications and marketing automation platforms (MAPs), as well as Web content management, event management and social tools. During the engagement process, leads enter a sales force automation (SFA) system, and sales reps access content on a sales portal or create a proposal using a configuration, pricing and quoting application.

Although each piece of sales and marketing technology may address specific user needs and contain diverse data, the information these applications contain ultimately relates back to the same group of customers, prospects, influencers and partners. Therefore, the data sets that these applications contain must relate to one another within the full spectrum of b-to-b sales and marketing technologies. Regardless of which technologies are in use, a few elements must be in place:

  • Hierarchy. Multi-level relationships are often used to model buying centers and reflect the relationships between parent companies, their organizations and individual site locations. Multiple applications can be used for this, each with a slightly different use case and perspective on the hierarchies (e.g. legal, sales, billing). Define how the hierarchy is being used in each application, then draw relationships between the hierarchies represented in each application.
  • Relationships. In each application, objects (e.g. contacts, accounts, opportunities) should be connected to one another through a series of primary key relationships. The most common example of this is using an email address to connect a contact in the MAP to the same contact in the SFA system. If such a relationship is not present, it is impossible to drive any type of combined marketing/sales intelligence.
  • Multiple identities. Contacts may have multiple identifiers (e.g. multiple email addresses, social handles) or none at all that uniquely identify them. Processes are required to stitch their multiple identities together to form a whole. This may involve the use of multi-part keys and the use of data brokers when relating records. It is important to resolve the issue of contacts with relationships to more than one account (e.g. CEO and a board member at another organization) or with two or more relationships (e.g. b-to-b and b-to-c) with the same company.
  • Lead management. Part of lead management addresses how net-new responses are entered into applications. Do they drive a net-new record (e.g. a unique lead), update an existing record (often creating an activity/campaign association to display the activity that occurred) or somewhere in between? SiriusDecisions recommends maintaining a unique contact record for each application, instead of using a point-of-interest (POI) or hybrid approach, given the reporting, data management and process issues that POI and hybrids create.
  • Data interchange. If the applications contain the same data elements (e.g. first name, last name, title), they must be able to pass data value updates to each other. This data interchange can occur via direct integration or through middleware that is connected to both applications. The key to this synchronization is deciding the source of truth when the same data element in each contains different values. Rather than attempting to identify an entire application as the source of the truth, look for the source of truth for specific data elements or sets of data elements (e.g. Web site interactions, firmagraphics, demographics, social responses).
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