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The four ”I”s of insightful market analysis

We’ve all come across market assessments that simply have not delivered the goods. For example:

  • Research that did not provide the required insights because it didn’t ask the right questions;
  • Surveys that were intended to provide a rich seam of material for a thought leadership programme, but that tell one nothing new or interesting; or
  • Studies whose findings couldn’t be relied upon because of either the paucity or poor quality of the underlying data.

Does any of this strike a chord? If so, the root cause is usually due to shortcomings in one or more of the following:

  • Project definition and planning
  • Information/data-gathering; or
  • Data interpretation.

The market assessment challenge

The key challenge in any market assessment exercise, regardless of its purpose, is to provide stakeholders with actionable insights, not merely information.

Insights enlighten the reader. They provide a degree of practical awareness and understanding that information alone does not.

Why this matters

This distinction between insights and information is an important management issue because market analysis plays a vital role in virtually all areas of business activity, both strategic and tactical. For example:

–          Strategy formulation requires a robust assessment of the available options;

–          Investment decisions need to be underpinned by reliable market due diligence;

–          Service line and new product development decisions require a deep understanding and awareness of customer needs and competitor activity; and

–          Thought leadership initiatives, to be worthy of the name, need to be based on genuinely new insights, knowledge and perspectives, rather than a rehash of what is already known.

It’s therefore in management’s interest that the market analyses which inform so many of their decisions and actions deliver as much value as possible.

However, market research studies often fail to hit the mark for one of two reasons: either they don’t provide the required answers or they fail to extract full value from the data.

Maximising the return on your market research investment

Significantly better, more useful outputs can be generated from market research studies by:

  • Focusing greater effort at the outset on defining the objectives and outputs required and how and by whom they will be used;
  • Giving more thought to how hard-to-get data might be obtained;
  • Analysing the data gathered more rigorously; and
  • Placing more emphasis on answering the question “What do the findings mean for our target audience and stakeholders?”

Three simple, yet powerful, tools for achieving this are:

  • The Four ‘I’s Market Analysis Framework – which breaks market analysis projects down into four phases of work – Identify, Investigate, Interpret and Infer – and ensures that all are geared towards achieving clearly-defined outcomes.
  • Deconstructive Investigation – a proven approach for obtaining hard to access, often commercially sensitive, data that can mean the difference between an OK outcome and a great one; and
  • The “So What?” test – a powerful technique for extracting maximum insight from the information assets generated during a project.

The difference between data, information and insights

The raw material of market research is data. At the very least, market research should provide useful information. Great market research, however, delivers insights.

What’s the difference? Chambers Dictionary provides some helpful definitions:

Data – “facts given (quantities, values, names, etc) from which other information may be inferred”

Information “intelligence given, knowledge”

Insight – “enlightenment, the power of discerning and understanding things, practical knowledge”.

The focus on enlightenment and practical knowledge gets to the heart of the issue:

Information interprets data and turns it in to something of value to the user.

Insights, however, use that information to provide the user with a level of awareness and understanding that the information does not yield up of its own accord. Insights cast new light on an issue. They provide new, practical perspectives that are based on evidence, rather than supposition.

The Four ‘I’s model, shown below, addresses shortcomings in project definition, data-gathering and data interpretation by ensuring that projects have clear objectives, focus on the right issues, gather the right data, and evaluate it rigorously.

It’s a powerful tool for making sure that market evaluation projects deliver robust, actionable insights, rather than merely information. The focus on insights is deliberate. Although information has some intrinsic value, it’s what you do with it that determines its true value.

The Four "I"s market analysis model
The Four “I”s market analysis model

The model splits projects in to four sequential, inter-related phases. It is built on the following principles:

  1. The lion’s share of the value delivered by a market study flows from the insights gained, rather than the information gathered during, the project.
  2. The quality of execution in any phase directly impacts the execution of the next. Importantly, poor execution of any phase will greatly reduce the value of the project’s outputs and potentially render them worthless.

Although the business need and outputs vary from project to project, insights gained typically deliver one or more of the following types of benefit:

“Hard” benefits “Soft” benefits
Clarity of direction Reassurance
Reduced risk Confidence
Competitive advantage Validation
Identification of opportunities Deeper understanding & awareness
Improved value proposition New knowledge

As will be seen, the model establishes a clear thread linking the project’s desired outputs (the insights), and all work elements in between, back to the underlying business need that gave rise to the project.

The Identify phase defines the purpose of the project precisely. It is the lodestar for the whole exercise. It sets the direction of travel by defining with absolute clarity the ultimate destination to be reached.

It sounds blindingly obvious, but unless you define from the outset exactly what outcomes you need from a project you’re highly unlikely to achieve them.

Key questions that must be answered at this stage include:

  • Who has commissioned the project?
  • What business need does it address?
  • What are the specific objectives of the exercise?
  • What are the “must have” outputs?
  • Who will use them?
  • How and in what situations will they be used?
  • What information do we already have which can be built on?
  • Realistically, can the data required to generate the desired outputs be obtained?
  • If not, what workarounds are viable?
  • What will success look like?
  • How will it be measured?
  • What other non-essential outputs would be of value?

So far, so good. The key point here is that, although these questions are obvious, the answers to them almost invariably are not. Unless you consider them fully and answer them precisely  you cannot shape a research approach that is fit for purpose.

Abraham Lincoln’s quote comes to mind:

“Give me six hours to chop down a tree and I will spend the first four sharpening the axe.”

The axe in question here is the market research specification and approach. Time invested at this stage, honing and sharpening it, will be amply rewarded. If you skimp this phase the project may well yield up information, but it almost certainly won’t deliver actionable insights that help take your business forward.

Asking at the outset “What will success look like?” is vitally important. It forces you to think beyond delivery of the research outputs to their desired impact and, therefore, to how they can best be used to achieve that end.

For example, the data capture and analysis protocol required for a study whose findings will be used primarily to produce a research report will be different to that for one where they will be used to generate bespoke benchmarking reports for specific target companies.

A good market evaluation specialist should make a major contribution during the Identify phase by helping you crystallise your thinking about exactly what you are looking to achieve. If you’re commissioning market analysis, whether from your own people or from external consultants, pay close attention to the quality of the questions they ask. The more searching they are, the more likely the specialist is to deliver the outcomes you need. If they’re providing neither constructive challenge nor suggesting ways of extracting greater value from the project, look for someone who can.

The objective of this phase is to gather the right amount (and no more) of the right data from which meaningful, relevant conclusions can be drawn.

But the devil is in the detail. The steps taken during the Investigate phase will largely determine the project’s success.

Projects can go awry for a host of reasons during the Investigate phase. For example:

  1. The wrong questions are asked;
  2. Essential questions are missed;
  3. The right questions are asked, but in the wrong way;
  4. The right questions are asked, but of the wrong people;
  5. Ambiguous wording makes responses difficult, if not impossible, to interpret; or
  6. The survey sample is not classified properly.

Often, the key barrier to overcome is that the data you need either does not exist or is not readily accessible. An example of the latter is getting access to commercially confidential information. Asking the question directly (an example of number 3 above) is unlikely to get a response – or at least, not the one you were hoping for! Deconstructive Investigation is a key technique for improving the quality of the data on which the project depends.

The power of DI – “Deconstructive Investigation”

Deconstructive Investigation is a powerful three-step process for eliciting hard-to-obtain information. The steps are as follows:

Step A: Deconstruct the issue – break it down in to its component parts.

Step B: Devise a means of getting the data you need for each element – often this will involve asking the required questions at different points in your survey instrument and/or asking questions of different stakeholders.

Step C: Combine the various data components to arrive at the required information.

This approach can be used to gather both quantitative and qualitative information. Here’s a real-life example of how we’ve used it:

Case-study: DI used in a corporate finance market assessment

The client:

A major corporate finance practice

Research objective:

To identify and prioritise potential corporate finance clients in an emerging UK high tech sector

Key data point required from target companies:

When will you run out of cash?

The research challenge:

To identify how much cash target companies had in the bank and their cash-burn rate. A small pilot study revealed that, although some companies would disclose this information, most would not.

How DI was used:

Deconstructed element:

Who we asked:

What we asked:

How much cash does the company have in the bank?


* When was your last funding round?* How much did you raise?* How many employees did you have at the time?

What is the company’s annual expenditure?




* What is your average annual cost per employee?* How many employees do you currently have?* What is your forecast growth in headcount over the next 12 and 24 months?


We were able to work out companies’ approximate cash-burn rates and estimate the likely timing of their next funding round.

Benefits to client:

* More effective use of budget – BD activity was targeted only on companies with a confirmed funding need.* Better timing of BD activity – ability to synchronise actions with companies’ financing cycle.* Cross-selling: identified opportunities for cross-selling employee benefits consulting services.

The approach used in the above study was entirely transparent, with the six DI questions spread throughout the survey questionnaire. Peer group comparators were used for any replies that companies declined to give.

We have used the same deconstruction/reconstruction technique to identify gaps in the risk management processes of fast-growth companies. This enabled one of our clients to accurately target its risk management consulting services on a bespoke basis at companies – and here’s the important bit – whose Boards were unaware, until approached by our client, of the gaps in their business risk management systems.

As these two examples indicate, employing Deconstructive Investigation can provide insights that deliver real competitive advantage. However, it requires commercial awareness, subtlety of approach, an astute research approach, sensitive drafting of any survey instruments used, and probably the application of carefully considered assumptions in the Interpretation phase.

A word of advice, though, from the former chairman of a FTSE100 food manufacturer, who is a firm believer in evidence-based decision-making: don’t seek out more data than you need in pursuit of spurious accuracy. Or, as he puts it:

“Better to be 80% correct than 100% wrong.”

These are wise words, particularly in qualitative research. It is often surprising how few interviews are needed in order to surface the key issues and nuances of thought around a topic. The payback from further interviews tends to tail off rapidly thereafter.

As can be seen, attention to detail is the key to ensuring that the first two phases of the Four ‘I’s Framework provide you with the rich and reliable data from which great insights can be drawn during the second half of your project.

The objective of this phase is to convert your dataset in to reliable information.

This should be a fairly simple task if you have complete and robust data to work with.

However, that’s rarely the case. Usually there will be gaps in the dataset, either because some of the data doesn’t exist or because what is available isn’t aligned exactly with what you need. Despite this, you can, with thoughtful analysis based on well-considered, defensible assumptions, generate good proxy information (i.e. information which is sufficiently reliable that high value insights can be drawn from it).

Reality-checking your provisional information – ideally using triangulation techniques -is essential at this stage of the project. For obvious reasons, the conclusions drawn from the study need to be based on information and assumptions that are free of obvious errors and flaws in the underlying logic used to generate them. For example, smart use of comparator ratios drawn from adjoining sectors or sample cohorts can be a good way of identifying potential errors or weaknesses in your proxy information set.

The golden rule in this phase, whatever, the nature of the project is: Listen To What The Data Is Telling You.

Don’t force it to say what you want it to say by manipulating it with inappropriate or over-optimistic assumptions. It’s a trap that some companies fall in to, for example, when preparing sales forecasts to support investment rounds. Reverse-engineering the data is a fool’s paradise and rarely pays off.

Finally, treat numbers given in off-the-shelf market research reports with caution, regardless of the publisher’s pedigree. Such reports rarely describe either the research methodology or the assumptions on which, for example, sector size or growth forecasts are based. It’s also worth checking, if given, the list of companies or demographics of who is included in the report as their criteria are often surprisingly inclusive or slack, depending on one’s view.

The objective of this phase is to enlighten your stakeholders –be they internal or external – by drawing useful insights, observations and conclusions from the project’s findings.

The power of asking “So what?”

The “So what?” test is an immensely powerful, yet simple, method of maximising the value derived from a project. However, it is often not applied as rigorously or determinedly at this stage of the process as one might expect.

For example, a major professional services firm publishes regular reports on private equity and VC technology investments. The firm’s objective, presumably, is to demonstrate that it has its finger on the pulse in the high tech financing space. They gather information from a range of public data sources and report it along the lines of “Levels of investment in sector X are up/down [select one] by Y% compared to the previous period”. This has some value as a curation exercise. However, they offer no meaningful analysis of why investment levels have changed or, more importantly, of what the potential implications are for interested stakeholders or of what the longer-term trends might be. The result is that the reports provide information, but no insight, only information.

If, however, the firm included the “So what?” question in their information analyes the reports would have significantly more business development value.

This raises two important points:

First, insights do not have to be conclusive in order to add value. The weight given to them will, though, depend on the quality and completeness of the information gathered during the Investigate phase and the analysis and judgments made in the Interpret phase.

Second, in some circumstances tentative conclusions and hypotheses may be the most that one can realistically infer. That does not, however, negate their value. It is far better to put forward an opinion, albeit tentative, as to what your research findings mean than to offer none at all. There is real value in putting forward ideas and observations that help stakeholders advance their thinking and consideration of an issue, provided the limitations of the source data are made clear.


Going the extra mile can radically transform the output of a market analysis project from mere information to high value-added insights that deliver real benefit to users.

Three of the most important tools in the market analysis kit bag to achieve this goal are the Four ‘I’s Model, Deconstructive Investigation and the “So What?” test.

Please get in touch if you would like to discuss how these tools can yield better insights for you from your market analyses and assessments.

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