Defining “Tiering an Analyst List”

Tiering is a process for segmenting an analyst list so that analyst relations (AR) can prioritize its activities. The most common labels are based on numbers (e.g., Tier 1, Tier 2 and Tier 3).  Tiering starts with a ranked list of analysts and then draws lines between analysts to create groups. Tiering is based on[…]

Defining “Ranking an Analyst List”

Ranking is a process for ordering a list of analysts based on formal weighted criteria. The criteria can include points such as research coverage, visibility (e.g., publications, press quotes, social media, speeches, etc), firm affiliation, geography, risk, and others. Criteria and weights are driven by the objectives of the vendor at both the business unit[…]

Defining “Analyst List Management”

Analyst list management is a process for identifying, ranking in priority order, and tiering into segments the analyst community. The purpose is to provide analyst relations with a tool for establishing analyst relevance and analyst relations (AR) team priorities. SageCircleSince 2000, SageCircle has helped analyst relations teams to focus on business value by encouraging innovative[…]

There can never be an analyst influence database [Practitioner Question]

question-mark-graphic.jpgQuestion: Is there a database that ranks analysts in terms of influence?

While there are some fine analyst directories or databases available for purchase (e.g., ARinsight’s ARchitect3) none of have “influence” data. This is because influence is a relative term which is dependent on what the vendor is trying to accomplish and the market space they are addressing. Obviously two companies with different products would see the same analyst as having different influence.  However, two competitors in the same market could also end up with analyst lists that are different because they have different business objectives they are trying to accomplish. Even the same vendor could rank the influence of the same analysts differently over time, even in a span of only a few months, as the vendor’s business and analyst relations (AR) objectives change.

While there are no databases of influence to purchase, AR can still create a formal analyst list management process with documented ranking criteria. Although this framework cannot eliminate the work associated with determining influence, it will permit AR to rank their analyst lists efficiently.

If an AR team does not have the bandwidth to do the work associated with creating an analyst list, there are […]

Cross-link your social media identify by adding your Twitter handle to LinkedIn profile

icon-social-media-blue.jpgIt’s important to raise the visibility of your Twitter handle to increase your followers, which could then give you insights about who you should follow. One of the simplest ways to raise your Twitter visibility is to place links to your handle in your LinkedIn profile. This is rarely done, but quite easy to do. 

SageCircle Technique:

  • On www.LinkedIn.com click on Profile then Edit My Profile then Additional Information to edit your websites
  • Select which of the three website slots to use
  • From the first drop down menu select “Other”
  • In the description box, type in […]

Interesting post by IBM’s John Simonds on back channels to analysts

Check out The Back Channel, My Most Important A/R Tool for useful tips on an important subject. One of John’s key points is to not abuse the back channel, but to use it judiciously. SageCircleSince 2000, SageCircle has helped analyst relations teams to focus on business value by encouraging innovative thinking that leverages insights and drives revenue. sagecircle.com

As we head into Hype Cycle refresh time, pick up a copy of “Mastering the Hype Cycle”

Gartner typically refreshes most Hype Cycles in June and July every year. From a timing point-of-view that means the analysts are starting to think about what they want to change in the Hype Cycle in April. Then in May and June they move into their serious work on their Hype Cycles in order to get them through Editorial by the end of June. Working backward that means that AR programs need to start now to think about how they want to influence the Hype Cycle. 

A valuable resource for AR programs that want to influence the Hype Cycle is the book Mastering the Hype Cycle: How to Choose the Right Innovation at the Right Time (Harvard Business Press, $19.77 + S&H on Amazon) by Hype Cycle creator Jackie Fenn and colleague Mark Raskino. While written for the enterprise client, there are many valuable insights in the book for vendor AR professionals.  Click here for SageCircle’s review of the book.

Related posts:

SageCircle Technique:

  • Add influencing the Hype Cycle to your annual AR Strategic & Tactical Plan
  • Carefully review the list of Hype Cycles to identify relevant targets (while there are 96 Hype Cycles as of July 6, 2008, this task will likely not require a lot of time and effort)
  • Identify which of your company’s leading-edge […]

Know when your analysts are likely on Twitter with Tweetstats

icon-social-media-blue.jpgOne of the great things about social media and Twitter in particular is that they give you permission to interact with analysts outside of the normal channels. This can be a powerful tool for staying top-of-mind because as former Gartner and AMD analyst Jonathan Yarmis tweeted: “vendors who interact with me on twitter get me multiple times/DAY, everyone else multiple times/month or year”. 

While you can tweet an analyst in an asynchronous fashion, it is even more powerful if you exchange tweets in real time. A great tool to understanding a person’s pattern for when they usually tweet is Tweetstats.

Tweetstats is a free tool that is simple to use because all you have to do is enter someone’s Twitter handle and hit [enter]. After a couple of minutes it returns a number of graphs that analyze the person’s twittering by date and time. Within this context it is the Tweet Density that you should look at because it shows when the person tweets by hour and day of week. Here are two examples:

Example A:
 Tweetstats - Tweet Density - example A

Example B: […]