Five Steps to Ensure the Best Integration Approach for Marketing Automation and CRM
Although the number of ways that marketing automation and CRM can be integrated is growing, different business setups can require different solutions.
Software providers increasingly build links into their products to meet common data transfer requirements, which is great for everyone. After all, why waste time and money developing data links that can be easily automated?
For instance, if you’re linking HubSpot and Salesforce the native HubSpot connector can do a great job of keeping marketing automation information and CRM data synchronous. Like most connectors, however, it has limitations, and these aren’t necessarily obvious at the outset of the project.
This is not a problem that’s unique to the HubSpot connector. To develop a dedicated link assumptions are made about data quality and structures and – more importantly – the business process. If a company doesn’t fit these assumptions, and the connector is not part of a larger framework of tools, significant business compromises are often necessary.
As the CEO of a company that provides integration solutions I’m probably more aware of this problem than most. My company has solved some difficult integration issues between systems such as Eloqua and Hubspot and various CRM systems such as Sage CRM, Salesforce and Dynamics CRM, so we’re used to advising when a standard connector will work, and when a deeper approach is needed.
Not surprisingly, it very much comes down to the types of data being transferred and being clear about the data flows associated with the business process. A typical challenge is the management of leads, which can be extremely complex and may also require a flexible update component for business owners.
Here are 5 steps we work through with the client (sometimes as a scoping project) to make sure fundamentals are clear and agreed before we make recommendations, quote or start any work. Nothing here is rocket science, but thorough attention to the basics means we are able to advise clients confidently on the best direction for their particular requirements, whether it’s a standard connector, a product such as our own, or a combination of both.
Step 1. Ensure all Relevant Business Units are Involved and Committed
It’s important to involve all players from the outset. No matter how thorough your Project Team is, if a business unit or a key person is not included it can have costly ramifications down the line as a result of missed, incomplete or inaccurate client data. For instance, marketing may be driving integration but if sales is not involved as well important lead allocation details can be missed. Such omissions can be due to ignorance about project scope or the result of internal politics; even if you have little control over the cause you can at least identify and flag potential problem areas.
Step 2. Make Sure the Client has Documented/is Prepared to Document Everything Being Transferred
The emphasis here is on the word everything. All too often the focus is on the main pieces of data being moved across, while areas such as pick lists can be easily forgotten. If you are moving client details, what sort of status types will there be in the destination system? Will details from other data repositories be needed to provide context? It’s tempting to gloss over things that look a bit tricky in these early stages, but ignoring them is not worth the potential headache they can cause later, so check and double check that your client has identified all data types and sources – or at least acknowledges gaps – before the project begins.
Step 3. Verify the Quality of the Data Being Transferred
This is related to the previous point. My company normally provides fixed price quotes, so we make sure we get visibility of the actual data before quoting. Users are so familiar with their own client details that they can’t see the wood for the trees – it’s rare that a business user can articulate the degree to which data is clean. Of course, this is especially the case when you’re transferring from a range of different sources because the same data may be represented in different ways and may also be duplicated. Check the data first hand so that you can factor data integrity interventions into the project plan, as needed.
Step 4. Clarify the Destination System’s Data Structure
Make sure your client understands how data will look in the system it’s being transferred to. Again, pick lists are a great example. You might be transferring clients flagged as hot, warm and cold, to where they are flagged as percentages. Or you could be moving clients that are not associated with a client to a system where they are. Differences in format, labeling and emphasis can change between where data comes from and where it’s going, and the extent to which this happens has ramification for the way the data is moved.
Step 5. Identify the Processing Steps Associated with Ongoing Integration
Once you know what data you’re transferring, how it needs to be whipped into shape and what needs to be done with it at the destination, you also need to look at any stops along the way. Will data need to be redirected according to user criteria? Does it only get sent once another job has completed? Will it need to go through Fuzzy Matching and exceptions be approved? Do duplicates need to be blocked? The complexity of these steps is often what determines the type of integration approach needed. The more atypical the treatment, the less likely a standard connector will help.
Clearly this process isn’t as easy as 1,2,3 – the above steps are interdependent and often revisited several times depending on the degree to which clients are prepared. Further, many processes are the client’s responsibility so often we have to be creative about how we guide and advise. At the very least, however, if we can’t be definitive about the entire transfer process we’ll get agreement on what needs further clarification, and also highlight any potential problem areas. It’s a strong place to start from.
As time progresses, more and more turn-key style solutions and easier data transfer mechanisms will become available. At InaPlex we’re already looking at the next generation of integration tools and will transform our own approach over the next few years. In the meantime, for at least the next few years, there will continue to be many complex integration projects requiring powerful, broad-spectrum, integration solutions such as our own.