4 Important Steps for Creating a MAP (Marketing Analysis Process)

4 Important Steps for Creating a MAP (Marketing Analysis Process)

We all want to come up with that big idea, actionable insight that will give our company competitive advantage and earn us glory.

But coming up with such an idea or insight is difficult.

To make things worse, an almost impossible way to achieve this is to sit in a room and brainstorm.

That’s why you need these four steps for creating a MAP (Marketing Analysis Process):

  1. Beginning with thorough planning.
  2. Collecting the right data to perform analysis.
  3. Analysis pointing to relevant & powerful insights.
  4. Reports telling stories that people will remember.

These steps are not easy and if you’re an analyst you know how challenging and difficult it can be.

All these steps link to each other, it’s a circular process and you learn along the way.

So let’s dive in!

1. Plan: define success

Establish your campaign’s or company’s clear, singular objective.

Good analysis starts with solid planning.

Defining a singular, clear and quantifiable objective is a good start. Now, ‘singular objective’ is the key here.

You can’t try to tackle different objectives, it will scatter your analysis and leave you without relevant results.

Be up front about this with your executive sponsor, your stakeholders or whoever it is.

Define key questions you will be asking of the data.

This is going to dictate what kind of data you require to answer those questions and then ultimately the sources.

So, getting those key questions right is very important.

Identify the type of analysis you will be conducting.

Identifying the type of analysis you’ll be conducting will also help you identify the type of data you need in your planning phase.

Document it all.

Finally, you need to put all the pieces together.

Document everything, so that you have your objective, your key questions, your analysis technique, types of data and data sources in a single place. This is your MAP!

2. Collect: measure what matters

Locate the sources which contain the required data identified in the planning step.

Remember you had this nice laid out document that takes you from your objectives, all the way to your data sources?

Now you’re going to find those sources and figure out how to pull the data.

Utilize data mining tools and techniques necessary to collect the required data.

You need the data mining tools and various techniques/tactics to pull the data out, and transform it into a usable form.

Select a data management system that balances your needs for power and simplicity.

If you think about that, there are so many systems out there, but which ones suit your needs?

The right question to ask here is how to balance the need that you have for the ‘analysis power’ of the program and the simplicity of use?

Usually the analysis power and simplicity of use are inversely proportional.

Something that is super powerful tends to be more complicated to use. Tools that are very simple to use, such as Microsoft Excel, probably don’t have as much horsepower behind them.

When you have your data, you need to decide which program gives you the right balance of power and simplicity.

Ensure the effectiveness of analysis by limiting bias in the data.

If the data that you’re popping into your data management system is poisoned with bias, the analysis that you produce is going to be poisoned as well.

The outcome of analysis is as reliable as the data you’ve collected.

3. Analyze: monitor and learn

Produce tidy, analysis-ready data-sets to ensure your analysis is error-free.

We’re looking to deliver those powerful, relevant insights that will compel our organization to change.

That’s why you need well-organized and clean data to make the process much more efficient and effective.

Proactively address data-quality issues and concerns.

There are always going to be data quality issues, nothing is going to be absolutely 100% perfect.

But if I have some data that is just directional, with enough marketing know how and experience I can make some kind of decision.

So, ensure that your data is as clean as possible, but don’t wait around for the “perfect data” to make decisions.

Perform analysis techniques that lead you to draw conclusions from collected data.

Different techniques have varying levels of depth and then they produce varying levels of insights.

Sometimes a simple analysis with a simple insight is all you need. Other times you’ll want to go a little deeper.

Compress your findings into easy-to-understand snippets.

Force yourself to compress the story you’re starting to form into a really tight and digestible little packet.

A great technique that you can employ is to ask yourself, how do I tell this story under 60 seconds?

If you can’t compress the story coming out of your analysis in those 60 seconds, you frankly don’t have a story yet.

4. Report: communicate and act

Leverage pre-attentive attributes in visual perception to quickly and effectively communicate your meaning.

This is a mouthful, but a few design tweaks and simple rules allow you to leverage those pre-attentive attributes to really get to your audience’s understanding.

Ensure that recommendations are as clear and concise as possible

Don’t leave room for interpretation or ambiguity.

Be clear and very concise about what you are seeing in the data, and then what is it that the organization needs to do as a result.

Follow simple rules of design to visualize insights with impact.

This post talks about those design rules and guidelines, if you follow them, then you’re sure to create visuals from which people can pull out meaning right away.

Connect your audience with passion to ensure your story is memorable.

You can start by understanding what your audience is passionate about and then crafting your analysis to fit into that area.

If they are passionate about something, they’re more likely to remember it.

It’s equally important that you express those insights with passion, so that it sticks with people.

Over to you

We saw that collecting the right data answers the right kind of questions, which leads to the insights we want.

We saw that the analysis must point out to relevant, powerful insights. It has to be relevant to your audience and it has to be powerful enough to compel them into action.

Then, finally, reporting should tell stories that people are going to remember.

As you build these reports, you’re also building an important base of information for your next planning phase.

Wish you all the best for your analytical journey!

Complete Guide To Planning The Perfect Marketing Analysis

Complete Guide To Planning The Perfect Marketing Analysis

Even before we begin planning our analysis, it’s important to keep in mind that the final result of a good analysis is not the result of one brief stroke of genius.

Instead, a good analysis is the byproduct of a painful and labor intensive process.

By the end of this article you will take away five important steps which will help you in preparing for the rest of your analytical journey.

These 5 steps can be categorized as follows:



5 steps for preparing the perfect marketing analysis

  1. There are five primary business objectives that your analysis can address, and choosing one of them is very important.
  2. The key question you are addressing for analyzing the particular data needs to tie back into those 5 business objectives. 
  3. A framework like CDJ (Consumer Decision Journey) produced by McKinsey is very helpful in categorizing and answering those key questions. 
  4. Once you understand where you’re going to direct your analysis, there are several tools available to help you in conducting it.
  5. Finally, documenting your plan is critically important for a long term success.
This is the overall layout which we explore throughout this article.

1. Five Primary Business Objectives

There are five marketing objectives that your analysis can address.



Five Primary Business Objectives


You need to select only one of these five before proceeding any further – which is very critical for conducting a successful analysis.

Even though your company may have multiple problems across many of these different objectives, but the analysis that you conduct can only be focused only on one of them.

Whether your goal is to build awareness, influence consideration, improve sales process, re-position your brand, or grow loyalty – all of these objectives are mutually exclusive, there is no real overlap between them.

And they really do cover the whole range of marketing challenges that an organization can have.

You will notice that growing sales is not on this list because that is not a marketing objective. Growing sales for an organization is an outcome of successfully addressing one of these marketing challenges.

So you may ask, how do I determine whether my organization struggles with one of these different challenges?


2. Key Questions Tying Back Into Business Objectives

Well, there are some simple questions that you can ask of these individual business objectives.

Build Awareness:

Do consumers recall and recognize my brand?

If they don’t, it means your brand has a problem with this business objective and you need to work on building your awareness up.

Influence Consideration:

Do the products that I have satisfy consumer’s needs?

If they don’t, it means consumers are choosing other products and you need to implement a better way to drive consumers to your products.

Improve Sales Process:

Do my sales efforts result in wins for my brand? 

If they don’t, there are probably hiccups or problems along your sales process that is causing issues.

And improving sales process doesn’t mean improving advertising. It’s rather about what you are doing at the shelf, whether you are winning or not?

For an e-commerce platform, once someone reaches the checkout process, are they completing it or do you have a large cart abandonment?

Is there something in that process that is preventing them from becoming a customer?

Depending upon the answers to these questions, you can tell if your brand needs to improve its sales process.

Re-position The Brand:

Do the experiences I deliver fulfill customer expectations? 

If they don’t, you either need to create products or set the expectations in consumers’ mind that your products or the brand that you promote, do actually fulfill their needs.

Grow Loyalty:

Do consumers advocate for my brand?

If consumers don’t advocate for your brand, then loyalty is probably the issue.

Now, these are the primary marketing objectives that organizations have and very few are able to address all of these correctly.

Not because an organization might have more than one problem, but because they try to analyze and tackle more than one objective.

As mentioned before, it will be critically important for you to find and settle on a single objective, because if you’re trying to chase too many, your analysis is not going to be impactful.

You’re going to get lost down that road!

3. Primary Categories of Marketing Analysis

Once we are done with deciding our primary business objective and key question tying back to it, we can now determine under which marketing analysis category does our situation falls in.

A great framework to help in determining that is the CDJ (Consumer Decision Journey) produced by McKinsey.


Let’s talk a little bit about how that works.

Everything begins with a trigger, either a customer sees an advertisement and goes wow, or they simply runs out of a product that they already have.

Following that is the process of active evaluation. It’s when consumers are collecting lot of information to evaluate the different product choices and brands.

The next step is the moment of purchase when a consumer is standing in the retail outlet – sees different products and has to make a choice.

After the moment of purchase, there is the post-purchase experience.

Then you’ve got a loyalty loop – place where every brand aspires to be. It’s basically a shortcut of the entire consumer’s decision journey.

If I am an advocate of iPhone, I’ll go to the nearest Apple store or place an order on Amazon for a new iPhone.

I’ll jump in that loyalty loop and avoid the possibility of buying some other brand’s product entirely.

This is the framework through which we can categorize the key questions of our marketing analysis.


You can notice the only one stage that is left out here is the trigger stage.

At the trigger, brands aim to gain awareness about consumer needs. Even though it’s vital for the success of any sort of brand, it is not necessarily a marketing challenge.

It’s more like that you don’t have the depth of understanding about your customers.

Now, for each of these different objectives and questions, a different analysis technique can be applied to gain insights from the data.


For trigger stage, clickstream analysis can be very important to see how consumers are moving around your website, where they’re going, what’s important to them and what is not.

At initial consideration data set, great insights can be gained by performing a competitive intelligence analysis.

Doing experimentation and testing is a good technique for active evaluation stage. Putting things into the market and pulling them out, then observing what the response is – AB testing where you offer two different choices to consumer and see which one wins.

Outcomes Analysis is a fantastic analytical approach for the moment of purchase. Which factors led to the purchase, or which ones caused the customer to abandon the purchase? Which factors caused them to go elsewhere?

Voice of the customer surveys are great ways to get insights into post-purchase experiences as well as collecting data around brand advocacy. Are consumers advocating for my brand?

A survey is a great analysis technique to learn more about your customer loyalty and their experience with your products.

4. Tools Available For Each Category

Tools that we have available to us are many and here’s my recommendation of some of the more prominent ones that are either low cost or completely free.

  • Clickstream Analysis: Google Analytics, Kissmetrics, Piwik.
  • Outcomes Analysis: Mongoose Metrics(DialogueTech) and LivePerson.
  • Voice of Customer Survey: Google Consumer Survey, Qualaroo.
  • Experimentation/Testing: Optimizely, AdWords Campaign Experiments and Google Website Optimizer.
  • Competitive Intelligence: Google Trends, Google Correlate, AdWords Keyword Planner.

By now you should be able to clearly see how we’re kind of layering in and building together the objectives, key questions that we need to answer on these objectives, and the tools that are available for the various analysis techniques.

But the most important thing to do is documenting all that so you’ve got laid out so far.

5. Documenting The Whole Plan

So, let’s walk through a quick example on how to do that. The documentation needs not to be fancy, just has to be simple and complete.

You want to document your business objective, tie that to a key question, and then identify data and sources.

So let’s take ‘Grow Loyalty’ as our example objective, here is what your document might look like.

One of the questions that we’ll want to ask then is, how has consumer interest in our brand trended over time?

Has it gone up or down? How have we been performing in terms of interest, which is a clear indicator of loyalty.

Now, this is your chance as a marketing analyst to get creative.

In this example we will use ‘Search Volume’ using Google Trends, which is an indication of interest. More search volume means more people interested in the brand.

Then we’ll also use our customer inquiries from our customer service representative database. Why is the consumer calling, did they want more product information?

The second key question we can ask is, what consumer group is our strongest advocate?

And to answer this we’ll want to look at a segmentation study that we already have. This study takes the different consumers that we market to and breaks them into discrete groups.

If we take Twitter as an example, then we can tie this segmentation study to Twitter usage statistics using Twitter API, to see which of these groups have tweeted out the most about our brand.

But Twitter is not going to tell us which of their Twitter accounts line up to which of our consumer segments.

So we’re going to be clever marketers and use hashtags in some way to tie people to different consumer segments.

Maybe we had them vote on what flavor they liked of our product – flavor being our segmentation method.

Third question would be, which marketing programs have grown advocacy for us?

And here we can use a couple of sources.

We’ll use our company website, which has the calendar of campaigns that we’ve run.

Again we must have been clever marketers, and probably asked consumers to use hashtags around those different campaigns.

Then we can check websites like Keyhole, which can provide for us the hashtag usage so that we can get a sense of the relative volume of Twitter activity that each campaign has created.

With this document in hand, we are ready to start out and identify the data sources and collect the data out of those sources – then conduct some analysis to answer our key questions.

Without this important document, we would be heading off on to a journey without a map.

And as you know, those never end well.

Let’s Wrap This Up

We covered up a lot of ground on this topic – talked about a lot of things.

So here’s an Infographic which boils down all the five steps of your data analysis plan. You can use it to recall the entire process.

Download this before you start off with your data collection and analysis journey.

Download Infographic for Planning The Perfect Marketing Data Analysis