Analytics: Understanding the Whole Picture

January 15, 2016


Data capture and the analytical information it provides is – potentially – a real game-changer in marketing, but many client-side marketers find that despite latest analytical methodologies, they still feel unable to apply this information to real-world market development.


It’s easy to understand why this is if one looks closely at the information they are attempting to work with, and this is often our first point of interest and focus when reviewing previous analytical strategies with newly-acquired clients.


The right data in the right hands?


McKinsey’s DataMatics study shows that firms in the top quartile of analytics performance were 20 times more likely to attract new clients, and more than five times more efficient at retaining existing clients than enterprises in the bottom quartile.


But while this at first glance sounds like data will offer some kind of silver bullet, the real question is: what kind of data is being utilised, how is it presented and – critically – to whom?


Too little data to go on?


The reality is that data takes many forms and these many forms can be compounded in many different and complex ways, leading users to draw conclusions that are very much at variance with the realities of their respective marketplaces.


For example, if you were to discover that your jelly-bean consumption survey data showed that everyone in the sample between 16 and 20 years of age had eaten jelly-beans and loved the colour pink it would be easy to assume that there was a strong correlation, right?


Data deficit or overload?


But what if this data hadn’t factored in the respondent’s income, and whether they could actually afford to consume jelly-beans in any meaningful quantity? That would mean many respondents in your data had a hidden and significant bias, so where would that leave your market analysis?


The fact is the data you are studying may either be too much data or of the wrong kind, with so much information that it not only confuses, but also actually lacks the critical information you need to target your prospects accurately.


Less is more


According to McKinsey, many analytics tools focus more on issues such as brand awareness, or different methods for measuring marketing return on investment (MROI), including stuff like reach-cost-quality (RCQ) performance, marketing mix modelling (MMM), or digital attribution modelling (DA).


And while each are useful in specific situations when used discretely to highlight specific market conditions, when used together they can provide conflicting outcomes that become difficult to understand, let alone use.


They become some kind of analytical gloop. So, you will need to ask yourself ‘why is my digital agency feeding me all this stuff?’.


Disconnected connectivity


Well, there can be a wide number of reasons for this but the most probable is a two-fold issue and this requires review: firstly, your agency – given that they are driving your marketing communications – should have had a clear definition of your target audience personas and an understanding of their behaviour.


If this isn’t in place, then the analytics data you will receive will not reflect market prospect and customer behaviour, market conditions or in any meaningful way help guide the buyer on their buying journey, meaning you (and they) are effectively flying blind.


Harvesting and targeting


If you find from this article that you are actually flying blind, then you need to implement the second tier of this marketing review: speak with those in your organisation who deliver marketing communications to your audience, and work with them to define exactly what they need to know about your target markets.


And that’s the first step along this part of the road: use this information to reach out to your front-line sales team and work with them to more closely define prospect and customer personas through objective evidence. This will close a very big loop.


Meeting of minds


Having now gained a clear insight into your markets, buyer personas and buyer behaviour from both a sales and marketing perspective, you now have the empirical market intelligence you need to brief your agency partners with an accurate picture of your market.


As you do so, ensure that this now closed loop stays that way – and ensure from here on in, your marketers and sales teams feed back regular market intelligence to you.


And when you provide this market intelligence to your agency, ensure they use it to reflect the real-world market intelligence your internal teams gave you, and reflect this in the data and analytical information your teams need to successfully connect with your prospects and loyal customers.


This post was originally published on the Novacom blog.

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