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Systematic Referral Selling

In a previous post I talked about “Referenceability and Introducabilty”— now let’s scale this.Path

In a previous post I introduced the concept of Connectors (people who can introduce you to Targets) and how to think of them in terms of Introducabilty & Referencabilty as well as how to ‘activate them”.

Can this scale?  Most people would say no.  In my experience, the answer is Yes.  How?  Starting with the obvious assumption that you have a great product or service and that most of the people who are in contact with it are impressed and would recommend it if asked, we first need to start systematically identifying these people.

Let’s start with some CRM hygiene.  Most CRM usage patterns don’t capture Contacts on the operational (post sale) part of the customer lifecycle,  yet have people in finance and purchasing (not good Connectors but were important for the initial business closing).  Start by rating who can say you are good– likely operational people are better than purchasing people.  You can take this a step further by using a product like Datahug to capture email connections from non-CRM users. You can even expand this to include people who were “pitched and interested” but for some reason did not buy your product.  This is point where you want to make sure someone in your team has a social network connection to each of these newly classified, valuable potential connectors.

Next, we can help these happy customers (Connectors) to remember who they know– look at their LinkedIn connections and find people who you think you could help (Targets).  Each Connector + Target combination is what I call a Path.  Quality and type of Paths can be classified and compared in order to find the best Targets to ask a Connector to introduce or the best Connectors to use to penetrate a specific Target Account.  LinkedIn team tools can help when looking at a Target Account, but the full task remains something that requires intensive manual research and organization to do this properly.

As we get new customers, we enlarge our Connector pool.  As they meet more people, the number of quality Paths increases.  Note that even if we don’t activate a Path by asking the Connector to introduce us, we can still use this information in the sales process as a reference.  The strongest possible reference is the one that appears randomly selected or is already a personal connection relevant to the prospect.

Some typical pitfalls:

  1. This will rapidly become a lot of research and very large amount of data.  (I had teams process more than 1000 LinkedIn connections per day and create researched Paths of more than 10 per day) Likely it needs a dedicated team within sales and some more advanced CRM customization + external tools. (Within one team of this type, I also had a dedicated engineering team making automation tools to assist this)
  2. Some connectors become uncomfortable when they learn that you are looking at their connections.  Presenting the approach to the Connector at the beginning is critical.  All the classifications, attributes, and lifecycle data about Paths and Connectors in your CRM is critical as you scale, but in the end, each and every request for an introduction required personal assessment of their personality and the nature of the relationship.  Well paid salespeople are usually the only ones appropriate to do this last stage of the process.
  3. You need to be very specific with many Connectors about how and why to make an introduction.  Also, your response is critical as well.  For example, when the Connector sends an email introduction with you on the CC, you should immediately (without waiting for the Target to respond) respond and take the connector out of the conversation in a professional manner (BCC– so the Connector can see that you are not abusing their intro).
  4. You need clear criteria on your ICP (Ideal Customer Profile) that includes attributes about the company and your target role– Industry, size of company, and locations are the easy ones.  I have used ratios around locations and job classifications as well as external data such as Crunchable funding.  Look at the premium LinkedIn account features to see if there are other filtering variables available.  If you are using dedicated researchers, you must impart knowledge about all the different descriptions for the same role (e.g.. CTO vs VP of Engineering vs CIO vs COO…)
  5. LinkedIn does not make this easy.  Their SDK is not useful for automating this.  Even manually, when you look at a Connector’s connections, they will present the list randomly.  If you stop and continue the next day, you can’t continue where you left off– you must do it non-stop for all contacts within a single session.
  6. This works best in countries, industries, and roles where LinkedIn (or Xing or Facebook) is active.



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