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  • Recent Posts: Kea SageCircle

    AR Classics: Identifying and Measuring Impact and Influence

    AR Classics: Identifying and Measuring Impact and InfluenceHow can analysts in non-traditional, freemium, analyst firms prove their value, and how should analyst relations professionals respond to their growing impact? Until analysts start to track their impact in the fullest way, they will always be underestimated by suppliers in the high technology and telecommunications industries. Back in 2015, when this was posted, Edelman’s Read more about AR Classics: Identifying and Measuring Impact and Influence[…]

    Investor relations head takes over AR at Tata

    Investor relations head takes over AR at TataThe IIAR is discussing a big surprise: one of the big 3 IT services brands just put its analyst relations (AR) under the control of its head of investor relations (IR). It would be unimaginable in most firms, and perhaps Tata Consultancy Services (TCS) is one of the few firms that can do that well. Tata Sons’ Read more about Investor relations head takes over AR at Tata[…]

    Peter O’Neill joins Kea Company as Research Director

    Peter O’Neill joins Kea Company as Research DirectorLONDON. February 1st 2018 — Longtime industry analyst Peter O’Neill has been appointed Research Director by Kea Company, the world’s largest analyst relations (AR) consultancy. O’Neill was previous research director at Forrester Research, leading the firm’s services for analyst relations professionals as well as research for B2B Marketing professionals.   At Kea Company, O’Neill will Read more about Peter O’Neill joins Kea Company as Research Director[…]

    AR Classics: Barbara French on how to grab an Influential Analyst’s Attention

    AR Classics: Barbara French on how to grab an Influential Analyst’s AttentionBarbara French’s Grab an Influential Analyst’s Attention: 3 Secrets & 4 Tips helps companies to avoid some of the most common errors in analyst relations. We especially appreciated these points in the article. Marketers can use analysts and analyst research to add credibility to their businesses without ever having the analyst specifically endorse their company. Read more about AR Classics: Barbara French on how to grab an Influential Analyst’s Attention[…]

    What research users can learn from analysts’ use of competitors’ analysis

    What research users can learn from analysts’ use of competitors’ analysisFor the first time, Kea Company is making reports from our Leaders Service generally available. The first discusses what research users can learn from analysts’ use of competitors’ analysis Although our Analyst Value Survey reports and Firm Awards exclude many analysts’ responses, this supplementary analysis suggests that many analysts are regular uses of research produced by Read more about What research users can learn from analysts’ use of competitors’ analysis[…]

Is it time to incorporate risk analysis into analyst list rankings?

Analyst Relations PlanningEvery AR team needs to manage their analyst list(s) to ensure they are focused on providing the right attention to the right analysts.  SageCircle stands on the “analyst list management” soapbox a lot because it such an important aspect of an effective and efficient AR program.  Creating a ranked list based on impact and then tiering based on available resources is the way to manage your service levels for analysts and ultimately manage your stress. There are many data points that go into an analyst ranking frameworks like visibility, research coverage, reputation, firm, geography and so on. This post is the opener for a discussion on whether risk should be added to the ranking criteria.

In this context, the risk being discussed is the potential damage to sales deals, market perception, internal politics, and such that can be caused by an analyst with a negative opinion. How much effort should you put into negative analysts?

So, should risk be incorporated into the analyst ranking framework as either a primary or secondary criterion? For instance, two analysts that are pretty much equal in all other criteria could see a negative analyst getting ranked higher than a positive analyst because there is more risk associated with the negative analyst and AR wants to invest more time to move that analyst’s opinion. If the two analysts are on the border between Tier 1 and Tier 2 Continue reading

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Defining “Analyst List Service Level Framework”

An analyst list service level framework defines the amount of resources that are available and the type and amount of each type that will be provided to any group of analysts as defined by ranking and tiering. For example, a service level framework will indicate which analysts receive one-on-one briefings from executives, get highest priority to getting their information requests handled, and are first contacted when major news breaks. Because service level frameworks reflect the amount of resources that the analyst relations (AR) team has available they must evolve as resources change.

Service level frameworks typically align with the tiers (e.g., Tier 1 and Tier 2) established by the analyst list management process.

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 AR resources (e.g., AR headcount, executive bandwidth for briefings, budget, et cetera). The fewer the resources the smaller the number of analysts that can be included in the Tier 1 group. 

Tiering is one step in analyst list management and follows ranking and is used to provide structure to the service level framework.

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 and analyst relations level. Criteria and weights should evolve over time as objectives change. 

While firm affiliation is an important data point, it is not the primary driver for analyst lists. Ranking should focus on individual analysts and not automatically give top placement for analysts employed by the largest analyst firms.

Ranking is one step in analyst list management and precedes tiering.