{"id":751,"date":"2015-08-13T17:33:00","date_gmt":"2015-08-13T16:33:00","guid":{"rendered":"http:\/\/www.telekta.com\/blog\/?p=751"},"modified":"2015-08-24T18:17:25","modified_gmt":"2015-08-24T17:17:25","slug":"systematic-referral-selling","status":"publish","type":"post","link":"https:\/\/www.telekta.com\/blog\/2015\/08\/systematic-referral-selling\/","title":{"rendered":"Systematic Referral Selling"},"content":{"rendered":"

In a previous post I talked about “Referenceability and Introducabilty”<\/a>— now let’s scale this.\"Path\"<\/a>
\n<\/em><\/strong><\/p>\n

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<\/a> as well as how to ‘activate them”.<\/p>\n

Can this scale? \u00a0Most people would say no. \u00a0In my experience, the answer is Yes. \u00a0How? \u00a0Starting with the obvious assumption that\u00a0you 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.<\/p>\n

Let’s start with some CRM hygiene. \u00a0Most CRM usage patterns\u00a0don’t capture Contacts on the operational (post sale) part of the customer lifecycle, \u00a0yet have people in finance and purchasing (not good Connectors but were important for the initial business closing). \u00a0Start by rating who can say you are good– likely operational people are better than purchasing people. \u00a0You 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. \u00a0This is point where you want to make sure someone in your team has a social network connection to each of these newly classified,\u00a0valuable potential connectors.<\/p>\n

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). \u00a0Each Connector + Target combination is what I call a Path. \u00a0Quality and type of Paths\u00a0can be classified and compared\u00a0in order to find the best Targets to ask a Connector to introduce or the best Connectors to use to penetrate a specific Target Account. \u00a0LinkedIn 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.<\/p>\n

As we get new customers, we enlarge our Connector pool. \u00a0As they meet more people, the number of quality Paths increases. \u00a0Note 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. \u00a0The strongest possible reference is the one that appears randomly selected or is already a personal connection relevant to the prospect.<\/p>\n

Some typical pitfalls:<\/p>\n

    \n
  1. This will rapidly become a lot of research and very large amount\u00a0of data. \u00a0(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)<\/li>\n
  2. Some connectors become uncomfortable when they learn that you are looking at their connections. \u00a0Presenting the approach to the Connector at the beginning is critical. \u00a0All 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. \u00a0Well paid salespeople are usually the only ones appropriate to do this last stage of the process.<\/li>\n
  3. You need to be very specific with many Connectors about how and why to make an introduction. \u00a0Also, your response is critical as well. \u00a0For 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).<\/li>\n
  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. \u00a0I have used ratios around locations and job classifications as well as external data such as Crunchable funding. \u00a0Look at the premium LinkedIn account features to see if there are other filtering variables available. \u00a0If 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…)<\/li>\n
  5. LinkedIn does not make this easy. \u00a0Their SDK is not useful for automating this. \u00a0Even manually, when you look at a Connector’s connections, they will present the list randomly. \u00a0If 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.<\/li>\n
  6. This works best in countries, industries, and roles where LinkedIn (or Xing or Facebook) is active.<\/li>\n<\/ol>\n

     <\/p>\n

     <\/p>\n","protected":false},"excerpt":{"rendered":"

    In a previous post I talked about “Referenceability and Introducabilty”— now let’s scale this. 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? \u00a0Most people […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-751","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/www.telekta.com\/blog\/wp-json\/wp\/v2\/posts\/751","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.telekta.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.telekta.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.telekta.com\/blog\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.telekta.com\/blog\/wp-json\/wp\/v2\/comments?post=751"}],"version-history":[{"count":7,"href":"https:\/\/www.telekta.com\/blog\/wp-json\/wp\/v2\/posts\/751\/revisions"}],"predecessor-version":[{"id":760,"href":"https:\/\/www.telekta.com\/blog\/wp-json\/wp\/v2\/posts\/751\/revisions\/760"}],"wp:attachment":[{"href":"https:\/\/www.telekta.com\/blog\/wp-json\/wp\/v2\/media?parent=751"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.telekta.com\/blog\/wp-json\/wp\/v2\/categories?post=751"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.telekta.com\/blog\/wp-json\/wp\/v2\/tags?post=751"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}