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Posts tagged ‘targeting & tiering’

10 things I’ve learned about AR & the analyst business – and that you should know too…

It’s that time of year when just about everyone in the analyst business and the broader technology industry comes up with their prognostications and predictions for the year ahead. Inevitably, many of those will prove wildly inaccurate, overly optimistic or simply embarrassing.

So rather than fall into that trap, I decided to cast my mind back and consider what I have learned about analyst relations and the analyst business in APJ over 10 years of running the only independent AR consultancy in the region (that milestone ticked over in November), working with dozens of vendor clients and engaging with hundreds of analysts.

Here’s my list. I’ve written about some of these issues before at length – you’ll find more detail on previous posts. And while I’ve thought a bit about the rankings, this is just my perspective. Don’t be afraid to give me your thoughts.

1.         It’s the relationship, stupid

AR is all about creating a two-way dialogue between a vendor and an analyst. Relationship builders take the time to understand the analyst’s interests & needs, and personalise the engagement accordingly, but they’re also pretty good at creating internal executive support for AR, which is when the magic happens. A good relationship builder with a weak story and/or content will mostly do better than an average engager with great content

2.         Most analysts are decent human beings

Yes, some are arrogant, anally-retentive or just downright difficult, but 99% of the time they’re trying to do the right thing for their clients. An engagement approach that recognises this can turn an adversary into an advocate. Analysts also need to have some relationship skills, and dickheads just don’t last.

3.         Vendors will continue to under-invest in APJ

I’ve written about this before, and sadly it’s just a reality of the technology business in this region – it applies as much to overall marketing & sales investment as it does specifically to AR. Vendors have a poor track record of making decisions at HQ which don’t take into account the growth & needs in emerging markets, and the current global economic situation isn’t going to change that. (But reading the goat entrails available to me, I feel cautiously optimistic that the needle is swinging back a little in 2013, after a very lacklustre 2012).

4.         Many vendors just don’t “get” AR – nor do some analysts

Some vendors will never “get” AR, simply because they don’t try to understand the value that analysts provide, or how they are differentiated from other influence communities. Their loss. On the flip side, some analysts fail to see that most AR professionals are advocates for analysts, not gatekeepers – despite all the evidence to contrary. It’s not a perfect world…

5.         Analyst targeting is the most important element of any AR program

Full stop. Understanding your audience is the cornerstone of any marketing or influence program, and AR is no different. Targeting is the first step, tiering is the second, engagement approach follows. All analysts have different needs & require different approaches, regardless of their prioritisation.

6.         Influence is global/regional, but engagement is local

Many analysts engage with clients right across the world, not just in their home countries or cities, and it’s important to understand where individual analysts have impact. But it’s much more important to engage with analysts in their own timezones. Regardless of how you manage that, you can’t assume that information will trickle down to an influential analyst who’s sleeping when you decide to run a briefing.

7.         Training spokespeople to engage with analysts is a no-brainer

Why wouldn’t you want to give your executives the best possible preparation for engaging with key influencers? Dealing with analysts is not that complex, but it is not innate, and spending a few hours upfront demystifying the analyst business yields immediate benefits and also avoids embarrassing outcomes.

8.         Measuring results is critical to AR success

You might consider this a bit self-serving, considering I provide a measurement program, but really – if you’re not measuring what you’re doing, then what are you doing? Don’t try to measure everything, and focus on measuring where you’ve actually influenced analyst perceptions – this is where you’ll demonstrate value to your internal stakeholders (and holders of the purse-strings).

9.         Some vendors will continue to confuse running analyst summits with an AR program

Sad, but true. An analyst summit is a one or two-day event which provides the opportunity to showcase your key messages, introduce some key customers, dig into some nitty-gritty around technology or go-to-market strategy, and develop relationships between key executives and analysts. An AR program is a day-to-day interaction process which ensures that analysts get the information they need, when they need it – and ensures those relationships prosper. To do the first without the second is a waste of time, effort & money.

10.       Change in the analyst landscape is a natural state

It is for every other business, so why not analysts? Firms will continue to grow & prosper. Some will be acquired because they offer something different, others because they have lost focus but retain analyst value and/or an interesting client base. Analysts will continue to become disgruntled with their employers, then quit to explore new markets, business approaches and delivery models. And so the cycle continues…

Just one more thing, which doesn’t require a number of its own…

In 2013, doing AR will continue to be fun/challenging/rewarding/ frustrating/boring/exciting/bloody hard work/just a breeze… Pick your adjective – it will be all of the above, and more, but the one thing I hope is that for AR pros and analysts alike : it will be worthwhile!! And fun, of course…

So tell me what you think. Have I missed anything? Would you rank these points differently?



How cloud, adjacencies & intersections are making the analyst business interesting again

Analyst firms have traditionally been structured in silos. In the past, this made sense – hardware was different to software, which was different to services. Breaking down just one of those segments as an example, PCs were different to servers, which were different to storage, and so it goes on….

The silos were a reflection of how products were sold (by vendors) and bought (by users). They were also a reflection of how research about those products was sold, and to whom. Many analyst firms – the big ones particularly – have done very well out of selling siloed, compartmentalised research programs to narrowly-focused product managers in vendors and technology specialists on the buy-side, slicing & dicing to match their specific interest.

The silo approach still works for (some) analyst firms – up to a point. But it’s started to break down over the past few years, and it’s going to break down even further over the next couple of years.

This is a good thing! Silos may be deep, but they’re narrow – and frankly, just a bit boring & artificial. I don’t think we’ll ever see them disappear, but the way that vendors market, sell & support technology continues to evolve, driven by changing preferences in how users buy & deploy it. And the same is true for analyst firms.

The largest analyst firms have started to break down the silos, to a greater or lesser degree. But it is the newer, more nimble firms which have most enthusiastically embraced the new order, partly because it provides them with differentiation, but also because that’s what their clients are asking for.

Probably the single most important factor driving this change is cloud computing, but it’s not the only one. Cloud sort of sits at the centre of this, but there are other adjacent “technologies” and “trends” which have a play – data centre transformation, mobility, application awareness, big data, broadband, social media, BYOD, always-on, possibly a couple of others…

But I’m not here to lecture to you about technology market dynamics – if I was, I’d still be an analyst! But these dynamics do have an impact on analyst relations, and how AR pros should go about engaging. From that perspective, I think it’s one of the most interesting periods I’ve been involved in over three decades of observing the tech space.

So what’s the upside, from an AR perspective?

 Access to a bigger audience

AR is not a numbers game, but it is a lot more fulfilling engaging with a number of experts than just a few. Service providers can now talk to software and telco analysts, software vendors can talk to mobility specialists, hardware vendors can talk to outsourcing analysts, and so on. Tiering is still important – within and across the silos – but you’re not restricted to core technologies.

Analysts get a little broader

Once upon a time, a storage analyst was a single-focussed hardware guy. Today, he might still be a hardware guy, but he probably covers servers and enterprise networking. He might also be developing a pretty good understanding of the infrastructure management software layer. The “old” handheld devices guru now covers a bit of network infrastructure, applications, security and service delivery models, as well as the device itself. Through necessity, analysts in APJ have always been broader than their colleagues in North America and Europe, but this trend is putting more structure around it.

 Analysts get a little better informed

Being exposed to these broader conversations has the potential to create better analysts. Context is important in understanding & explaining the deployment of technology, so looking and thinking outside the silo adds depth to the advice that they provide to clients.

But what’s the downside?

 Analysts sacrifice depth for breadth

There are already some analysts who try to be experts about everything, and there is a danger that more analysts will start providing commentary outside their areas of expertise. Deep domain knowledge is where analysts can add value, and that will be eroded if they allow the pendulum to swing too far.

Too many opinions from one source

Diversity of opinion is one of the great benefits of a competitive analyst business, but there needs to be some consistency of perspective within individual firms. Some firms are better at collaborating than others, and it’s important that analysts whose coverage intersects or abuts with others are actively communicating & collaborating with their colleagues. They don’t have to agree 100 per cent, but two perspectives which are poles apart within a single firm tend to destroy the credibility of both.

Targeting gets more difficult

Putting analysts in a single box has always been tough, and probably a little dangerous. These days, you need to map analysts right across your portfolio, and across your adjacencies. You’re still going to tier them with your usual methodology, and it’s going to take more time, but in the process, you’re probably going to learn more about them.

Like all things in technology and the analyst business, this isn’t black-and-white. There are lots of fuzzy edges, but what else do expect in a market which continues to evolve? For mine, it makes the analyst business much more interesting than it was a couple of years ago, and I’m pretty sure it will continue to be for the next couple of years – at least!



Inside the black art of analyst targeting & tiering

In my last post, I concluded that analyst targeting isn’t evil, just necessary. So why continue with the necromancy theme?

Because targeting & tiering is a black art – it’s part knowledge, part experience, part intuition. It can be taught, but it’s certainly not a science. Targeting is a process, and like any process, it has a series of steps.

 Topic triage

This is the easy part. There are thousands of analysts worldwide, but you want to exclude those that have no relevance to you. The simplest way is to develop a short list of keywords which are relevant to your business. Say you sell CRM software that includes some business analytics capabilities, then you might choose “CRM”, “salesforce automation” and “business intelligence” as your keywords. If you have tailored solutions for specific industries, you might add “government” and “supply chain” into the mix. If you have a cloud-based delivery model, you might want to add “SaaS”, for example.

But don’t get carried away with too many because you’ll spread your net too wide. If a solution accounts for only a small percentage of your business and isn’t a growth or focus area, ignore it. Be careful not to get too specific with your keywords – unless you’re looking for deep insight in a narrow field – or you run the risk of screening out everyone.

AR program objectives

This is the definition part. What are you trying to achieve with your AR program? Are you trying to build market awareness, what my colleagues at KCG call exposure? Or are you trying to reach analysts who have direct influence over technology purchasing decisions? Do you want to engage with market or technical experts who can help you with your competitive positioning? Are you looking for firms who’ll produce sales collateral for you? Whichever way you plan to go, you need to understand your goals and align accordingly.

 Research, research, research

This is the time-consuming part. Whether you’ve got access to a commercial database such as ARInsights’ ARchitect or an internal analyst list, you’re going to need to add to your knowledge before tiering your analysts. Use your keywords to narrow your search. Most analyst firms publish analyst bios on their websites, and most allow you to search at least the titles of research they’ve written. The quality of this information – and its usefulness – varies considerably, but it’s stuff you need to know. Look more broadly – at LinkedIn profiles, social media usage, media articles they’re quoted in, conferences they’ve presented at and whatever else you can turn up. Learn from it, but don’t take it as gospel.


This is the interesting part. As part of the process of defining your AR program objectives, you made some decisions – consciously or otherwise – about the type/s of analysts you want to engage with. This means that certain analyst behaviours and characteristics are more important to you than others, and you need to weight them accordingly. If you care about direct user influence, then analysts with large end-user enquiry loads will be more important; if you want to drive media exposure, you’re going to value media-hungry analysts higher; if you believe strongly in the power of social media, you’ll be looking more closely at the Twitter junkies.

Pick your criteria – usually five to six is enough – and evaluate your analysts accordingly. Rate them, rank them, throw darts at them – how you do it is up to you. Most AR pros use a spreadsheet or database to enable sorting & searching, but one of my clients has me mapping analysts onto a Boston Consulting Group chart (think Gartner’s Magic Quadrant framework) which is a remarkably powerful way of visualising analyst value, particularly when educating senior executives.

Some analysts will naturally float to the top, but most won’t.

Experience & intuition

This is the fun part. What you have so far is lots of information. What you don’t have is clear answers about which analysts are really the most important and influential.

Most of the information you have at this stage is flawed or incomplete. Boilerplate bios on analyst websites tell you what the analyst thought s/he covered when s/he started the job, not what s/he actually does now; LinkedIn profiles are bloated with self-serving achievements and vague references; published research titles give some insight into coverage, but not much about depth of domain knowledge.

There is no substitute for experience. And applying it to the information you’ve gathered is where the science turns to art.

Over the years, I’ve engaged with hundreds of analysts. Some have worked with me; a few were clients before they became analysts; many have attended briefings I’ve organised; others have participated in interviews for my AR measurement processes; with too many to count, I’ve shared meals, coffees & drinks in cafes, hotels, airport lounges, breakout rooms, and everywhere in between.

During those interactions, we’ve learned much about each other, and developed trust in many cases. It is the insights from those interactions that I’m able to apply to the tiering process – knowing the types of clients they really work with, what their workload looks like, the way they engage with senior executives, the types of questions they ask, the depth of their domain knowledge and so much more.

Quite simply, I’m more comfortable making a judgment call about an analyst I know well than one I don’t. But what if I don’t know the analyst? Well, experience & intuition still have a role.

You need to be able to read between the lines. Simple things like analyst titles, reporting lines, co-authors, media profiles all tell a story, but you need to know what you’re looking at. So all that information that I said was flawed or incomplete still has a value, if only you know how to interpret all the different pieces.

To target & tier effectively, you need to make judgment calls, and that only comes with experience. You can’t teach it, but you can learn it.

But what do you think?



Analyst targeting isn’t evil – it’s just segmentation

Many times over the years – usually over beers – my conversations with analysts have turned to how and why AR professionals choose to work with some analysts, but not others.

Most of them take it personally if they’re not considered “Tier 1” by all and sundry, but the fact is that most of them don’t understand the rigorous processes that many AR pros use to assess the influence and importance of analysts. Many analysts don’t understand their own value propositions either, but that’s the topic for a discussion on another day.

Analyst targeting & tiering is the foundation stone of any AR program. If you don’t understand who your audience is & why you’re talking to them, then frankly, you’re just wasting your time.

Of course, lots of other issues come into play – like resourcing & budgeting & reach & content & more. But when you’re building an AR program, you always have to start with the who & the why.

Why target?

Vendors sell products, solutions & services. Some sell a wider range than others, but at the end of the day, they’re only of interest to some people, not everybody. If you sell soft drink, you can take out ads on television & the web and pretty much reach your target market (backed up with some clever social media campaigns that enhance the impact of your key influencers).

If you sell technology, your market is more limited. And if you sell a specific type of technology, then your market narrows even more. So does the number of observers, analysts & commentators who care about your product/solution/service.

Targeting is first and foremost about identifying analysts who are interested in what you sell. Why engage with people who don’t care about what you do?

 Why tier?

All analysts are not equal, nor do they all do the same thing. Neither are journalists, or indeed customers. Marketing is all about segmentation, so it constantly amazes me that vendors dump analysts into a single bucket, when they’d never do the same with journalists or even media outlets. (It also constantly amazes me that some vendors dump analysts and journalists into the same bucket – and expect the same outcomes – but if they’re doing that, they don’t understand PR or AR!)

Would you treat the senior technology writer from a national business daily read by A & B demographics the same as the editor of a monthly publication that focuses on a particular technology segment? Of course not! Would you tell them the same stories? Probably not. Would you expect different outcomes? I hope so.

So if targeting is all about defining your audience, tiering is simply about evaluating the importance of the various members of that audience.

 How do you go about targeting & tiering?

Like many things, that depends on who you are and what you’re trying to achieve. I’ll save a detailed discussion about targeting & tiering approaches for another post, but in short, it all comes down to what you want to achieve.

If you want to use analysts to help build your credibility with end-users who purchase your solutions, then you’re going to target one group of analysts, some of whom will share similar characteristics, many of whom won’t. If you want to use analysts to help improve your positioning in signature “market landscape” research, then you’re going to target another group; and if you want to use analysts to help build market awareness by writing about your solutions or talking to the media or conference audiences about you, then you’re looking at another group again.

If you want to do all of these things – and many vendors do – targeting & tiering becomes even more important, because you simply won’t have the resources and bandwidth to achieve all of these objectives equally, or even effectively.

So targeting & tiering is all about compromise, but in a positive way. It’s about focusing on which analysts are going to give you the best outcomes, depending on how your objectives are prioritised.

I’ll get into the detail of the tiering & targeting process in another post, but I’d love to hear your views in the meantime. Is analyst targeting evil, or just common sense?