I’m continuing my series of blog entries where I am sharing some early results from REPAMATron – my automated competitive marketing intelligence gathering tool. In this entry I’m looking at the difference in marketing strategy between open source and closed source enterprise service buses (EBSs).

REPAMATron automates my REPAMA competitive marketing intelligence methodology and is currently in Alpha. I’m using the ESB market, a market I know well, to help to tune the algorithms at the heart of REPAMATron.

In my previous entry I looked at 3 Enterprise Service Bus vendors’ marketing strategies (WSO2, Talend and FuseSource) and compared them to the computed market mean. I’ve now added another 6 ESB vendors to the study from the long list of ESB vendors produced by Gartner. These new vendors are TmaxSoft, JBOSS, Axway, Seeburger, JBOSS, InterSystems and iWay. So the complete list of vendors and products currently under scrutiny is:

I’ve also categorised the list into open source and closed source ESBs. This has allowed me to pull together Marketing Element Distribution (MED) charts that show the difference in marketing strategy between the average open source strategy and the average closed source strategy.

Which features are important for Open Source ESBs versus Closed Source ESBs versus the ESB average?

The PIPESCOM Marketing Element Distribution (MED) chart below shows the features that are promoted most prominently by vendors in the ESB space. Each of the 3 chart series shows a different market mean. The ESB market mean shows the 12 vendor average of all of the vendors in the table above. The closed source ESB vendor average features the average of the 7 closed source vendor results whilst the open source ESB vendor series aggregates the results of 5 open source vendors.

This is an interesting set of results for a couple of reasons. Firstly because there is a great deal of similarity between the open source and closed source vendors. Taking an ESB to market, be it closed source or open source, appears to be about focusing on communicating the same basic set of features. Interfaces, process and management features are all promoted strongly in keeping with the very nature of an ESB.

However, a number of differences (differentiation) exist. As one might expect the open source ESB vendors place extra emphasis on the packaging of their product as well as the commercial characteristics. There is also an additional focus on ease-of-use by closed source vendors although the reason for this is not immediately clear. It appears that closed source vendors believe that stressing the ease-of-use characteristics of their products is more important than their open source contemporaries.

Which value propositions (benefits) are important for Open Source ESBs versus Closed Source ESBs versus the ESB average?

The MITICOR Marketing Element Distribution (MED) chart below shows the value proposition (benefit) categories that the vendors in the study stress in their outbound communication. The chart series are as described in the PIPESCOM chart above.

Again, this is an interesting set of results. It appears that when it comes to expressing the value (or benefit) that the vendors feel they deliver to their customers there is significantly more differentiation between open and closed source ESBs than with the PIPESCOM features chart above.

Also of interest is the Cost value proposition. As you’d expect this is where a vendor feels they can save, reduce, offset, mitigate of remove cost for their customers. One would naturally think that an open source ESB proposition might focus heavily on the cost benefits of an open source solution over a comparable closed source ESB. The chart above bears this out in that the open source Cost proposition scores higher than the closed source equivalent. However the difference is very small and the Cost value proposition for closed source vendors already scores strongly. This would suggest that with their closed source ESB counterparts already focussing on the cost benefits of their solution, it will be difficult for the open source vendors to differentiate and sell using cost alone as a proposition.

In my next blog I’ll share the results of a direct comparison between an open source ESB vendor and a closed source competitor. I’ll also continue to add vendors and additional tests to these studies and will share the results in future blogs.

Please post any feedback you may have in the comment section below or contact me here.

Danny Goodall

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In the previous post I shared some of the early results from REPAMATron – the technology I’ve developed that automates the process of gathering competitive marketing intelligence.

The previous post described what REPAMA and REPAMATron are all about so if you’ve landed here and have no idea what this is, then I’d recommend that you read the first post in this series. Having taken a look at how a section of the Enterprise Service Bus market (WSO2, FuseSource and Talend) communicates benefits or value propositions, I’m now going to share the research into the product features that each vendor communicates most prominently. To allow a comparison to be made between the vendors and to the market mean (the average strategy of all vendors in the segment), I first have to examine how each vendor communicates product features and determine which of the PIPESCOM categories the feature fits into.

What is PIPESCOM?

The PIPESCOM classification allows one vendor’s marketing copy to be compared to another’s with respect to how they communicate product features. This is achieved by categorising the features that are described in the vendor’s marketing copy into the following broad categories. Packaging, Interfaces, Process, Ease of use, Speed, Commercial, Operational, Management. So for example, if a vendor describes their product as having “the ability to interface with other systems” then that would suggest they are making a claim about the product’s Interfaces. If a vendor talked about their product being available as a service then this would relate to the Packaging category of PIPESCOM. Similarly if the product is described as ‘inexpensive’ or ‘commercial-off-the-shelf software’ then that would fall into the Commercial category. You can read more about PIPESCOM here.

PIPESCOM (Product features)

The following series of charts shows the relative support for each of the PIPESCOM product feature categories found in the vendor’s marketing materials. The esb market mean displayed in the chart is the aggregate or average strategy of the 6 Enterprise Service Bus Vendors in the table below.

This market mean allows a comparison to be made between the results of WSO2, Talend and FuseSoruce and the ‘average’ approach vendors take to the Enterprise Service Bus market.

FuseSource

^*The chart below shows that FuseSource stresses the interfaces the product has to other technologies. This is not surprising since an ESB exists to interface to other technologies. That said, it is clear that FuseSource’s reliance on communicating Interface features is much higher than the esb market mean (the aggregate of the 6 ESB vendors above). FuseSource does not focus on ease of use, or at least not significantly enough to register with REPAMATron.

Talend

^*Talend’s product feature focus mirrors very closely the esb market mean. The exception is that Talend focuses significant effort on ease of use features – significantly more than the market mean.

WSO2

^*WSO2 shows an above average focus on packaging (the way the product is configured for sale/use) and the management features of the product. Similarly to FuseSource, WSO2 places little discernible focus on the ease-of-use features of its products.

FuseSource, Talend and WSO2

^*The combined chart shows how each vendor stresses different product features in their outbound marketing. The differentiation between them and to the esb marketing mean is shown by their relative commitment/lack of commitment to one of the PIPESCOM categories. It appears that differentiation exists between the vendors around how Packaging, Ease-of-use, Commercial and Management features are communicated.

In future posts I will expand on the vendors in this ESB study and will also share some additional MED and text analysis tests. I’d welcome feedback about vendors that should be included in these studies and indeed what market segments I should look at next. In addition to rounding out the ESB study I plan to look at high performance messaging and master data management as I am working on client projects in those areas at the moment. Please post feedback in the comment section below or contact me here. Danny Goodall ^* – This is alpha software. The results and conclusions are indicative at the moment and are in no way definitive.

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If you’ve been following this blog you’ll know that I analyse the marketing tactics and strategies of high-tech vendors – mainly in the infrastructure software space. It’s…

…an emotional day for me as I share the first output from my automated competitive marketing intelligence gathering system – REPAMATron. Well perhaps it’s not that emotional, but it certainly represents a significant milestone in a project that has been in development in my ‘spare time’ for a little while now. Below you’ll find my first tentative steps at automated analysis of the Enterprise Service Bus market.

REPAMA is a research methodology that allows me to categorise and compare the marketing strategies of high-tech vendors inferred from the language they use to take their products to market. REPAMATron automates this manual methodology and generates competitive marketing intelligence that allows competitive differentiation to be visualised and benchmarked.

Before I share the first research results, here is some of the background alternatively you can go straight to the research.

It’s Alpha. It’s Alpha. It’s Alpha.

Taking inspiration from Google’s legendary ‘Beta’ logo that it uses so well to reflect a bit of geek chic onto their latest features, I feel the need to do the same. The difference is that one suspects that Google’s beta code is pretty much commercial quality with a beta label stuck on it for marketing purposes, but with me it’s important to say that this really is alpha software.

The technology and logic behind REPAMATron is at a very early stage. The rules that it uses to determine whether a vendor is following a certain strategy or not will be continually refined over time and as such it will take a little while until results stabilise enough to be ‘accurate’. That said the general inferences that it arrives at are broadly accurate today.

What’s the big idea?

This is competitive differentiation Visualised and Benchmarked.

Visualised - I wanted to create technology that would visualise the competitive differentiation between different vendors’ products within a given market segment. This is especially important in markets where little apparent differentiation exists between the competing vendors. Developing REPAMA taught me that even amongst vendors that have broadly similar products; the way they describe, promote and generally take their products to market can be very different indeed. I wanted to develop a system that could identify ‘hidden’ differentiation and present it graphically so that it could be easily understood.

Benchmarked – By grouping together the a number of vendors’ results it is possible to create an average set of results – I refer to this as the market mean. It is then possible to benchmark and compare each vendor’s strategy to this market mean as well as to specific competitors in the market segment. Understanding how your own strategy differs from the market mean or from a specific competitor can be a very valuable insight.

How does it work?

If I told you that I’d have to kill you. But in general terms, ScrewTinny, the technology behind REPAMATron collects examples of marketing communication from vendors – usually marketing and product collateral from web sites, press releases, emails, etc. This text is analysed using phrase matching, natural language processing and statistical likelihood methods to determine if a specific marketing strategy is present or if a specific claim is being made. All of these inferences are then processed as if being read by a human so text found on popular web pages ranks higher as does text near the top of a document as do multiple clusters of the same inference, etc.

There are currently two main types of analysis. MED Charts and TextAnalysis charts. TextAnalysis charts are not shown below but I will post more on them in a future blog entry.

What is an MED Chart?

The MED Chart (Market Element Distribution), is used to show the relative commitment a vendor has to a specific strategy. A score of 11^* is apportioned, or distributed across the various different marketing strategies in the chart. Vendors that focus their marketing communications on a small set of strategies are rewarded with a higher score. However vendors that water down their focus by aiming at many strategies will score less for each strategy.

Let’s take an example of a two vendors that are describing the value proposition (the benefits) that their respective products confer. Let’s say that vendor A makes one claim repeatedly that his product reduces the cost associated with some task or other. Vendor B also makes repeated claims that her product reduces cost, but in addition she also claims that her product will increase her customers’ revenue and will also reduce the risk of project failure.

Now both vendors make a value proposition to their audience associated with reducing cost but for vendor B her cost claims are watered down because she also makes additional claims about value propositions (or benefits).

What is MITICOR?

MITICOR is my acronym for defining the major categories of value proposition. Think of MITICOR as capturing the category of benefit that each vendor believes their product provides. Broadly speaking I have categorised business to business value propositions for infrastructure software into the following broad categories: Market, Income, Time, Institution, Cost, Operational, Risk. So a Market value proposition might be a claim that you will increase your customers’ market share or that they will get some form of competitive advantage whilst an Institutional value proposition might instead talk about delivering improved company image or reputation, increased shareholder value, better corporate governance, etc. You can read more about it here.

What PIPESCOM?

So if MITICOR captures the claimed benefits associated with a product then PIPESCOM captures the features that the vendor communicates most prominently. As I explained in this previous PIPESCOM blog entry, it’s difficult to compare vendors product marketing strategies without first trying to categorise the types of features that are promoted.

PIPESCOM allows one vendor’s marketing copy to be compared with another vendor’s by categorising the claimed features of the product into the following broad categories. Packaging, Interfaces, Process, Ease of use, Speed, Commercial, Operational, Management. So for example if a vendor describes their product as having “the ability to interface with other systems” then that would suggest they are making a claim about the product’s Interfaces. Similarly if the product is described as ‘inexpensive’ or ‘commercial-off-the-shelf software’ then that would fall into the Commercial category. You can read more about PIPESCOM here.

What’s Next?

I’ve only automated a couple of the 20+ different studies found in the manual REPAMA methodology so I will add those that can realistically be automated. In addition having access to statistical information about the marketing copy that each vendor uses opens up many more possibilities that can’t, or at least can’t realistically be done manually.

The Research

When looking at the vendor comparison below please bear in mind that I’m not looking at the actual capabilities of the products – this isn’t a product review. Instead I’m looking at the marketing claims each vendor makes for the capabilities of their products as embodied in their outbound marketing communications.

As I mentioned in a previous blog post I chose the ESB market to help hone and develop the algorithms behind REPAMATron because it is a market I know well. I will continue to add vendors from this long list of ESB vendors over time and ultimately will cover all market segments in infrastructure software, but for the moment the vendors and products included in the analysis are:

From that list, the Talend, FuseSource and WSO2 results are shown below. The esb market mean comparison that is shown on the charts is the notional average of all 6 ESB vendors from the table above.

The charts are interactive in that if you hover over or click the various datapoints you should be able to see the specific values.

MITICOR – Value Propositions (Benefits)

The following series of charts show the value propositions or benefits found in each vendor’s marketing copy. The MITICOR charts show the relative importance that each vendor attaches to that category.

FuseSource

^**In the chart below it is clear that FuseSource stresses the cost and operational benefits of its software. No other value proposition was found that scored highly enough to be recorded in the chart. This shows a clear focus which interestingly, is quite a departure from the market mean of the 6 ESB vendors. Fuse Source’s focus on Cost is considerably higher than the market mean whilst their their claims about the operational benefits of the product is considerable below the market mean.

Talend

^**Talend’s value proposition appears to centre completely around Operational benefits. Any other value proposition that might appear in its marketing copy didn’t register highly enough to score on the chart. This type of result, where a only single value proposition is recorded is quite common amongst vendors that focus on features without linking them through to benefits that their customers might derive from the feature.

WSO2

^**Interestingly, WSO2′s value propostion most closely follows the market mean. The implied benefits for WSO2′s products are that they will save time, reduce cost and improve operational efficiencies.

FuseSource, Talend and WSO2

^**The combined value proposition chart for the three vendors shows the differentiation found in their marketing materials – differentiation between the 3 vendors in the chart as well as differentiation versus the the ESB market mean.

Well that’s the MITICOR value proposition charts, I’ll post the PIPESCOM product features analysis in a separate blog entry.

I’d welcome feedback about vendors that should be included in these studies and indeed what market segments I should look at next. In addition to rounding out the ESB study I plan to look at high performance messaging and master data management as I am working on client projects in those areas at the moment.

Please post feedback in the comment section below or contact me here.

Danny Goodall

^* – Why 11? Everyone knows that the best amplifiers go up to 11.
^** – This is alpha software. The results and conclusions are indicative at the moment and are in no way definitive.

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I wrote the other day about the need for a Technology Reading Ease Index. I’ve been thinking about how it might work so here are my current thoughts.

The problem I am looking to solve is that I want to be able to rate the readability of different technology vendors’ marketing copy. As I explained here, traditional readability indexes do a good job at rating the complexity of text, but do not recognise the domain knowledge that the author expects a reader to posses in order to understand it . So I’ve decided to build something on top of the existing readability indexes that takes into account the frequency and density of technological acronyms that are used.

This technology reading ease index will go through a few iterations before it’s fit for purpose I’m sure. For example, in addition to looking for acronyms, I think I could also add specific technological terms too. But for the moment I’ll simply look for acronyms.

So here is a list of the design criteria for a readability index that measures traditional readability measurements (word/syllable complexity, word length, etc.) as well as the degree of technical knowledge and domain expertise required to understand a specific text.

1. Must take a representative amount of text – minimum length of say, 300 words
2. Should count the total number of acronyms found
3. Should consider the number of different acronyms that are found
4. Should ignore the length of the acronym itself (I don’t believe that there is a correlation between the number of letters and the complexity of the acronym)
5. Should use the density of acronyms found in the text (acronyms per 100 words or something like that) as the basis of the rating
6. The index should be able to be used separately from other readability indexes as well as in addition to them
7. The index should not try to compute a ‘grade years’  equivalence as other generic readability indexes do. Instead it should produce a rating that needs to be interpreted.

So ideally I will reach a rating that describes the amount of domain-specific knowledge the reader would need to posses; and by combining that with a generic readability index such as Flesch-Kincaid, Gunning Fog, Coleman-Liau; I will reach an overall rating for readability and domain knowledge.

The question is how to construct the result and how to interpret it. I’ll keep you posted.

Danny Goodall

P.S. The image in the top right was created by wordle.net and shows an acronym soup.

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The answer is…well at the moment I don’t know but I know a way of finding out.

One of the by-products of the REPAMATron system I’m building to automatically infer a high-tech vendor’s marketing strategy from the way they take their products to market, is that I’m able to build a count (or frequency distribution) of the words that are used in their marketing literature. If I also know what grammatical category (part of speech) the word fits into (noun, verb, adjective, etc.), then I can build a count for the different parts of speech associated with describing a product or service.

This might be useful for example if we look at the superlatives (best, fastest, quickest, cheapest, etc.) or the comparatives (better, faster, quicker, cheaper, etc.) that are associated with a product or service. Why is this useful? Well for marketeers that take competitive marketing strategies seriously, its useful to know just how  a competitor is claiming to be different/superior to their competitors. And it is through the superlatives and comparatives that they use that we will be able to answer the question “Just how do they think they are better?”.

So whilst I don’t know the answer to the question above at the moment, as part of the automated competitive intelligence study on Enterprise Service Buses that I’m building, I will soon.

I’ll keep you posted.

Danny Goodall

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As I mentioned in a previous post I’m in the process of automating REPAMA – our competitive marketing intelligence methodology. It’s quite a task and I’ve not been able to focus as much time on the project as I would have liked, but it’s coming along.

REPAMA visualises competitive intelligence. I created the REPAMA methodology to allow me to understand infrastructure software vendors’ marketing strategies and to allow me to compare one vendor’s strategy with another. REPAMATron is the project that is automating the manual REPAMA methodology. It’s going to take a number months to work through all of the algorithms to ensure that they are true to the manual REPAMA methodology. But I thought I’d share some of the early output and at the same time address something that is bugging me at the moment – how to represent the Market Element Distribution (MED) studies graphically.

Those familiar with the manual REPAMA methodology will know that I have historically represented the Market Element Distribution charts as spider (or radar/spoke/polar) diagrams. I used Excel to produce the charts and as you can see from the chart below this results in an interesting way to represent the relative commitment/lack of commitment to each of the specific elements of the marketing strategy.

Excel-Produced Radar Chart - Example MITICOR MED Study

The greater the commitment to a specific element of marketing strategy, the longer the spoke in the chart. For example, my MITICOR study looks at the how much emphasis a vendor places on each of the 7 categories of Value Proposition that I monitor (Market, Income, Time, Institutional, Cost, Operational, Risk). Therefore if I find evidence that a vendor leads with a value proposition around reducing expenditure (Cost is the ‘C’ in MITICOR) and has a minor commitment to increasing revenue (Income is the first ‘I’ in MITICOR), then the spider chart would feature a long spoke for Cost and a shorter spoke for Income – as shown for Vendor 2 in the example chart above.

Using Excel allowed me to ensure, through manual adjustment that each chart was readable. Even if the chart featured data that occupied the same area I would be able to adjust colour, shading or line size to make it easier to read. However, now that a program is producing the chart I no longer have the luxury of a pair of human eyes to fettle the appearance.

The result is a spider chart that can be a little busy and difficult to read as shown below.

Radar Chart - Example MITICOR MED Study (Automatically produced by REPAMATron)

In addition the charting library that I’m using doesn’t support radar charts with smoothed (spline) lines. As a result the radar features angular lines which again makes it slightly more difficult to read than it’s Excel smoothed-line cousin. (As an aside, Excel 2010 also has a problem with smoothed lines on radar charts).

So I’m looking at alternative charts that still show the relative commitment to different elements of marketing strategy but perhaps show them a little more clearly. Here are some of the ones I’ve looked at.

Spline Chart - Example MITICOR MED Study (Automatically produced by REPAMATron)

100% Stacked Column Chart - Example MITICOR MED Study (Automatically produced by REPAMATron)

100% Stacked Area Chart - Example MITICOR MED Study (Automatically produced by REPAMATron)

Line Chart - Example MITICOR MED Study (Automatically produced by REPAMATron)

Stacked Bar Chart - Example MITICOR MED Study (Automatically produced by REPAMATron)

100% Stacked Bar Chart- Example MITICOR MED Study (Automatically produced by REPAMATron)

Stacked Column Chart – Example MITICOR MED Study (Automatically produced by REPAMATron)

The style that I am currently favouring is the Spline Chart (as shown on the right). I think this really clearly shows the different strategies of the vendors in the study and the resulting spline line produces a signature shape for that vendor’s strategy.

That said in early testing I have had some feedback that this sort of chart should not be used to show discrete data values in a series, but instead is better used to show the flow between different data points – i.e. identifying the delta between previous and subsequent data points.

So if I’m not going to use the spline chart then I think I’m leaning toward the Stacked Column Chart (as shown on the left). So I will take more soundings and think on it some more.

In order to tune the natural language process engine at the heart of REPAMATron, I’m going to focus on an area of the infrastructure software market that I know well – the ESB segment. I must stress that the charts and tables that I’ll post in this and future blog entries will be Beta versions because the required algorithms and statistical analysis are not fully developed.

REPAMATron is currently designed to automatically build a series of PowerPoint slides so in subsequent blog posts I will share some PowerPoint output whilst the algorithms are tuned.

Danny Goodall

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…Well strictly speaking that should be I’m creating a monster. You see, I’m in the process of automating our REPAMA methodology. Let me explain.

I’ve been using the REPAMA competitive research methodology for many years to understand vendors’ marketing strategies. Long before the formation of Lustratus in fact. It wasn’t a strict methodology back then. It was a set of relatively loose processes, measures and classifications that I used to ‘score’ various elements of a specific software vendor’s marketing strategy.

I used the process when I worked on the vendor side in various senior marketing positions. It allowed me to understand how I could differentiate my company’s technology from our competitors. And to differentiate, first I had to know how my competitors took their products to market.

I then used it to good effect in my marketing consulting engagements where I was able to advise software vendors how they should go about competing with other vendors in the market. I was able to provide an in-depth knowledge of their competitor’s go-to-market strategy – the sort of thing you only normally get by employing someone from a competitors’ organisation (after taking NDAs and employment contracts into account of course!) .

I’m sure that in an informal way most marketeers do the same. You’re reviewing a competitor’s marketing material and you’re trying to build a mental picture of the strategy behind the words they use. You ponder…

Which companies, in which segments do they target?

Which job roles are they looking to communicate with?

What product features do they promote most heavily?

What value do they claim to provide and how do they believe that they are different from their competition?

How similar are they to ‘us’?

How are they generating their sales leads?

etc.

Under the Lustratus brand I’ve been able to inject some structure and rigour into the process and I’ve given it a name – REPAMA or Reverse Engineered Positioning And Messaging Analysis. I now produce formal REPAMA Segment Analysis Studies for vendors who want to understand the marketing strategies and tactics of a vendor, a group of vendors or across a specific marketing segment. This they believe gives them a great advantage in their planning. All is good.

However, as the REPAMA Guide shows, it’s a complex process and it takes a quite some time to produce a formal REPAMA report. There is a great deal of planning, reading, analysis, categorisation, re-categorisation, scoring, ranking and documentation before the formal report can be produced. Add to this the fact that vendors’ strategies and tactics change all the time and it is quite a task for a single Marketing Analyst to keep abreast of a number of market segments.

So earlier this year I started to investigate how I might go about automating the process of producing this analysis. How, I pondered, might a piece of software be able to help me to ‘read’ and analyse examples of vendor marketing communication to produce the REPAMA reports? And so it was that Project REPAMATron (excuse the working title) was born.

Since then, I’ve been working through an external organisation to build the logic and process of my competitive analysis methodology into their software. The early results have been very encouraging and whilst it will be a little while before we’re going to be able to publish any research, we’re not far off being able to share some of the early results – hence this post.

The software is based around the techniques that search engines and other automated language based system use – namely NLP or Natural Language Processing. NLP strives to derive meaning from the otherwise apparently random collection of characters that computers use to represent text. NLP algorithms need to be ‘trained’ and the more language they see, the more accurately they can determine the meaning behind a collection of words or tokens. So at the moment there is a lot of ‘learning’ and tuning to be done.

Once the engine is designed, it is then a question of what form the published analysis might take. Currently I manually produce PowerPoint presentations and formal reports and I suspect that might be the first route I take with the automated analysis. But with the relative ease at which this information can be mined, it might be that I provide access to the analysis through some form of web-based on-demand search interface. It also means that I might be able to provide access to some of the base REPAMA information free of charge. And those are two characteristics of a search engine. And whilst I’m not talking about a general Google competitor here, it could be that a search engine for competitive marketing intelligence is getting a little closer.

Danny Goodall

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I just can’t help myself. No seriously, I have no choice here but to introduce yet another acronym but at least this one doesn’t have three letters. So how did PIPESCOM come about and what does it mean?

Our REPAMA methodology compares and contrasts different vendors’ marketing approaches by reverse-engineering their positioning and messaging strategies. To facilitate easy comparison between vendors we must be able to categorise the way they approach different elements of their marketing strategy. And with that categorisation I’m afraid, comes acronyms.

To categorise how a vendor creates its value propositions we introduced MITICOR that denotes that a value proposition typically claims to deliver benefits that broadly fall within the following areas – Market, Income, Time, Institutional, Cost, Operational and Risk.

To categorise how a vendor approaches the decision making unit we introduced IGIDBU – to show the Initiator, Gatekeeper, Influencer, Decision maker, Budget holder and User elements of the decision making unit. We didn’t create these elements as many before us have worked on defining the different roles with the decision making unit. We simply stood on the shoulders of giants and then wrapped yet another acronym around them.

So, PIPESCOM? One of the issues we face when comparing infrastructure software and hardware vendors’ marketing approaches is in understanding when the arguments they provide to their prospects about their claimed features are similar or contrasting to those of their competitors. Obviously, in isolation one claimed feature such as…

“…supports XML”

…can be seen as very similar to…

“…supports content-agnostic encoding”

for example. But when comparing 3 or more vendors’ claimed features it becomes more complicated. The answer, for us at least, is to create categories into which each of the claimed features can be placed. Comparing vendors’ product strategies then becomes a case of comparing the categories their respective claimed features fall into. In the example above we might say that both vendors are making a claim for how their products interface with the outside world.

PIPESCOM is the first draft of our categorisation of features. To be honest, I found it pretty tough to arrive at a categorisation that encompasses all of the capabilities we’re likely to come across in infrastructure software/hardware. I didn’t want too broad categories or too narrow so this is my first cut. As I take the technique to other areas of the infrastructure software/hardware market, and perhaps beyond, I’m sure PIPESCOM will be changed and adapted.

I guess I should at least include a definition of what I mean by “Feature” here. So for me a feature is a dispassionate and discrete fact about a product or service that does not seek to persuade. This definition is close to that used in Spin Selling and will be familiar to anyone who has looked at that methodology. Importantly a feature is not an Advantage or a Benefit.

The letters represent the following elements.

Packaging, Interfaces, Process, Ease of use, Speed, Commercial, Operational, Management.

I will be including PIPESCOM related research in the next release of the methodology but first I have to stress test it to ensure that I’ve included the correct categories. After all, today’s PIPESCOM could be tomorrow’s PIPESCOMXYJPQEWXMN.

But let’s hope not.

Danny Goodall

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I’ve just uploaded the first draft of my latest Cloud Computing REPAMA Segment Analysis Study.

This time I’ve looked at a couple of vendors in the Cloud Software / Cloud Management / Application Services Management segment (using the Lustratus REPAMA Cloud Computing market taxonomy / segmentation model). Specifically I’ve reverse-engineered the key go-to-market strategies of 3Tera and Appistry. I will add another couple of vendors to the study as time goes on but for the moment I thought these would be two good candidates to start with. They are very different companies with very different product approaches to solving similar, if not quite the same problems. I wanted to spend a little time here highliting some of the interesting findings.

Differentiation

I’ve already blogged on my concern that Cloud Computing vendors/ providers are currently differentiating themselves against previous paradigms as opposed to creating differentiation strategies versus their real competitors – i.e. other cloud computing solutions. So it’s no surprise to see that this trend continues in this study with 3Tera. Looking at where 3Tera fires its competitive differentiation fire power in the UNLIKE element of the positioning statement we can see that the focus is:

traditional dedicated infrastructure

To be honest this is an implied competitor/alternative because whilst 3Tera is very clear on its value proposition and target audience, it doesn’t appear to engage in traditional competitive differentiation. Nowhere does 3Tera clearly define what type of solution they feel they are a better alternative to. There is an obvious implied competitor / alternative which is the traditional ways of doing things. But this is never called out explicitly by 3Tera.

Appistry is clearer on its competitive situation. It believes that its competitive differentiation lies versus:

infrastructure approaches to cloud computing

The implication here is that Appistry focuses on the application and not the infrastructure which they believe yields many benefits.

Existing Applications

One area of strong correlation between the vendors in this study is that they both stress their ability to work with existing applications. This correlation suggests that this is a key customer requirement in this particular market segment. As shown in the chart below:

As you can see from the dashed pink line on the chart above (which represents the market mean – the average marketing strategy for this segment) there is strong support for existing applications in addition to the somewhat obvious “table stakes” feature of automated application deployment and management.

Value Proposition

Another strong area of correlation is in the value proposition. The first chart below shows the raw claims made by each vendor for the value they ascribe to their product offer.

Much of these categories of benefit/value are fairly generic and are all very similar to the the value propositions I would expect to see for a cloud computing product. When these value propositions are interpreted against our MITICOR value proposition classification, we can see a very strong correlation between the products of the different vendors as the chart below shows.

The value proposition for both of these products boils down to operational improvement and cost saving which again is very much as I would expect for a cloud computing technology in this segment.

Positioning Statements

I’m not completely 100% happy with either of these positioning statements as both of these companies appear to aim everywhere and focus nowhere. This lack of focus is important to note in itself as it is common in immature markets, but it does make nailing down a semi-accurate reverse-engineered positioning statement a little tricky. But here they are:

3Tera AppLogic Positioning Statement

FOR organisations looking to deploy successful online services to millions of users WHO are struggling to manage the complexity of the infrastructure required to serve online services to online users OUR AppLogic IS A grid operating system for web applications THAT PROVIDES the ability to assemble existing software into portable applications that run on any grid and scale from a fraction of a server to hundreds of servers with a single command UNLIKE traditional dedicated infrastructure OUR PRODUCT makes it extremely easy to deploy scalable web applications without dedicated IT resources and personnel

Appistry CloudIQ Platform Positioning Statement

FOR enterprises seeking to take advantage of cloud computing WHO need to migrate existing applications to the cloud and virtualized environments OUR CloudIQ Platform IS A Cloud application platform THAT PROVIDES enterprises with the ability to move multiple existing applications to the cloud and manage them across multiple cloud environments UNLIKE infrastructure-focussed approaches to cloud computing OUR PRODUCT allows existing applications to be packaged and deployed to a cloud without re-architecture

Both statements are weak in the target customer and their respective pain, need or desire reflecting the lack of clarity in their outbound marketing.

Slides

I’ve placed a slide deck which expands upon this research on Slideshare.net and this is embedded below. If you’d like more information on this study or a copy of the slides, please contact me. Details of  how to interpret REPAMA studies can be found in the Lustratus REPAMA Guide here.

Danny Goodall

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I’ve been working on a way of categorising value propositions for some time. I’ve arrived at something I refer to as MITICOR which I believe represents the atomic value proposition elements.

By this I mean that all business to business value propositions can be broken down into these 7 base elements. I’m sure I will refine this over time but for our purposes these elements allow us to analyse and categorise the different value propositions that vendors use in their go-to-market efforts.

So what do these categories refer to?

Market

Elements categorised as “Market” include value propositions that relate to the organisation’s market or competitive situation, new product or service introduction as well as the organisation’s marketing efforts such as awareness, public relations or image.

Income

“Income” includes any offer that proposes to increase or sustain existing revenue. In addition new revenue streams fall into this category.

Time

“Time” relates to any value proposition that reduces the time it takes to achieve some organisational objective. Importantly this does not refer to reducing the time to achieve a tactical objective as this would likely be categorised under Operational below.

Institutional

Institutional value propositions relate to the organisation as an entity. Chief amongst these are value propositions that deliver value to shareholders. Taxational or political issues such as “green” policies also come under this heading.

Cost

Reduction in costs, offsetting costs and cost restructuring all fit under this value proposition category.

Operational

Propositions that deliver positive changes to the operational efficiency of the organisation come under this classification. Included in here would be propositions that provide visibility into the current operational effectiveness of the organisation.

Risk

The removal or mitigation of risk at a corporate, personal or project level falls under this value proposition classification.

Multiple Categories

Specific value propositions that vendors create will break down into one or more MITICOR category. It may be that a value proposition from a vendor relates to only one MITICOR category but it is likely that it will break down into more than one MITICOR category.

Examples

I’ve listed below some examples of vendor value propositions and the MITICOR categories that they break down into.

I wanted to document this classification in this blog because I will refer to them in future REPAMA research. I’ve also noticed during the course of my research that there are some very predictable value propositions/MITICOR element combinations. In a later blog I will try to document these MITICOR “chains” and specifically how they relate to the members of the decision making unit (DMU).

Danny Goodall.

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