Tag Archives: big data

big is great but smart is better – a big data discussion

I have recently had the chance to listen to a presentation by Phil Winters at the CRM Expo in Stuttgart. Phil is an active advocate of big data theories and a very lively presenter (can only recommend to sit in if you have the chance). Anyway, one of Phil’s slides caught my attention particularly.  A slide about a very basic but yet, as it seems, mostly ignored principle about big data.


In other words, BIG DATA – NON-IDENTIFIABLE DATA SOURCES = SMART DATA. The grid used to present this is about as easy as it gets but holds all the value a smart marketer needs to step into the big data discussion.

1) Visualise your customers purchasing decision making process (or the funnel if you want)

2) Identify touchpoints (this alone is a great exercise for most marketers and even more for internal service providers – customer centricity is the key – not what you want)

3) Assess data availability per touchpoint (is data readily available, in which form, when, from whom etc)

4) Assess smart data options (can you make sense of the data or identify user groups or even single users out of a specific data set)

5) Identify the data creator (is it a customer, potential customer, noise etc)

6) Smart Data entry (can you make sense of underlying values, behaviours or motives – in other words, can you interpret the data gathered at this level)

More from Phil Winters here – enjoy the read and happy smart data mining (I am a big advocate of logical naming conventions and from that point of view, big data is a misleading term, we don’t need big data but smart data; think about it!)

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If the sky isn’t the limit anymore… what is?

Redbull’s Stratos campaign has set a new dimension of campaign and social engagement with consumers around the world. It also sparked discussion about the terms paid, owned, earned and shared media, however seldom has somebody questioned if the reach for the stars and current campaign scopes are still in line with resource theories of the firm. I argue they are not, excess capital holdings allow certain organizations to device campaign stunts, driven by eager agencies to score the next big thing, without establishing a full campaign to business objective link.

Watch somebody jump from space vs. going to space yourself (Axe Apollo):

YouTube Preview Image

Questions that should be raised by marketers and budget holders:

> Is the race for the most extreme campaign to gain a healthy and sustainable race?

> Is it just too easy to spend money on paid media to get audience attention through extreme campaigns vs. meaningful content stimulation throughout the customer journey?

> Are campaigns like Stratos and Axe Apollo really justifiable beyond the hype of press and bloggers? Shouldn’t we as marketers not look beyond total reach and claim target audience reach in meaningful numbers? What is it that we achieve with campaigns? Can we create meaningful links towards the bottom line? I argue big media allows us to do so but at the same time introduces campaign limits.

> As most marketing organisations are setup as cost-centres, don’t we have an obligation towards stakeholders and the firm to justify our spending even more so these days?

> Are we just making use of aggregated fluffy terms like earned or shared media to hide behind walls of agency influence and ego stipulation to have the biggest campaign? Does size really matter in that sense?

Paid, earned, owned and shared isn’t what is seems like – we need to dig deeper:

If we spend $20m on a campaign and estimate to reach x number of people on the premise of paid media, y number of people on the premise of owned and z number of people on the premise of earned and zz number of people on the premise of shared; do we really measure what is meaningful to the brand, to the bottom line and to our budget responsibility? Shouldn’t we segregate reach into current customer reach and potential customer reach, furthermore increase in sustainable purchase effects and short term campaign spikes? Furthermore, I argue that smart data allows us to construct a media model which assigns values to each theoretical nod, we can start to differentiate between dead-end reach, multiplication reach and bottom line effective reach.

Dead-end reach: non current and non-potential customers, low network degrees

Multiplication reach: non-current or non-potential customer with a value generation network degree, e.g. one or more nods are either customers or potential customers

Bottom line effect reach: the total of current and potential customers reached through the conglomeration of paid, owned and shared. This number should be in a healthy relation to both substitute media spendings (e.g. $ effort) and also the total number of people reached. If we assume our target reach is equal to a sample population, the sample to total population ratio becomes a statistical ratio and the marketer’s task is to find the sweet spot instead of trying to cover the entire population to also reach the target group by intersection effects.

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