Mariamz

Posts Tagged ‘measurement

In a recent post Haowen Chan and Robin Morris warn “the last thing you want to do is implement a [big data] system that develops and propagates data, only to learn it’s hopelessly biased.” All research and analysis has bias built in by the very nature of human involvement. However Chan and Morris provide four useful bias-quelling tactics that can be used to improve the big data science process:

  • Employ domain experts Rely on them to help select relevant data and explore which features, inputs and outputs produce the best results. If heuristics are used to gain insights into smaller data sets, the data scientist will work with the domain expert to test the heuristics and ensure they actually produce better results. Like a pitcher and catcher in a baseball game, they are on the same team, with the same goal, but each brings different skill sets to complementary roles.
  • Look for white spaces  Data scientists who work with one data set for periods of time risk complacency, making it easier to introduce bias that reinforces preconceived notions. Don’t settle for what you have; instead, look for the “white spaces” in your data sets and search for alternate sources to supplement “sparse data.”
  • Open a feedback loop This will help data scientists react to changing business requirements with modified models that can be accurately applied to the new business conditions. Applying Lean Startup like continuous delivery methodologies to your big data approach will help you keep your model fresh.
  • Encourage your data scientists to explore.  If you can afford your own team of data scientists, be sure they have the space and autonomy to explore freely. Some equate big data to the solar system, so get out there and explore this uncharted universe!

We can also consider what bias we are encouraging when we develop systems – from social media plugins to smart objects – which collect ‘big data,’ or data which could be aggregated into big data analysis. Might we be unfairly representing a picture from our data subjects, either by representation or omission? Collection, processing and analysis are all crucial to consider in the quest for useful and accurate big data outcomes.

Image of what the Internet looks like via Flowing Data – the work of Peer 1 Hosting & team

Mark Ritson recently wrote, If you think Oreo won the advertising Super Bowl with a tweet, look at the social media scoreboardIn this, he puts forward a bold position: firstly that social media reaches a relatively small number of people, in a relatively light way (in comparison to TV ads) and secondly, that “The players might have changed, but the game has always been the same.” I’d like to briefly tackle these sentiments with some counter-points:

  1. Two-way, multi-way, a new way:  It’s a standard social media point to make, but it’s seems it still must be. The game is not the same, because we are talking about many to many communication, about instantaneous interaction between publics and brands. Broadcast media (print, tv and to a great extent radio) was about crafting messages and pushing them out. Social media is about stakeholders, customers, innovators, product developers, consumers, suppliers, shareholders, customer services getting under eachother’s skin in real-time. It means a wealth of chances to make better products, services, institutions and outcomes, and for a brand to know, in no uncertain terms, whether it is delighting, inspiring, boring, horrifying, losing or poisoning its target customers and (former) audiences faster than ever, ever before.
  2. Broadcast reach vs reach on the brand’s terms: According to Ritson’s calculations, the Oreo tweet reached 200,000 people, which he compares with the 8 million Americans who eat an Oreos cookie during one year. But these sums ignore that social media engagement does not rest on one tweet alone, however brilliantly improvised its content. If an individual likes a brand enough to follow it, to endure its posts, by choice, day in day out – that brand has a chance of reaching that number of people, with what it chooses, on its own terms, and over and over again. It does not have to pay per placement, negotiate partnerships with publishers or pitch to journalists. It decides what to say and how to say it, and gets it out there immediately. And what happens on Twitter doesn’t stay on Twitter.  According to Exact Target, discussions that begin on Twitter are more likely to appear elsewhere on the web than they are from any other network.
  3. Tiny stories versus big bangs: Ritson challenges the value of Oreo’s tweet on the grounds of its ‘potency’, because he is apparently wedded to the old-school marketing obsession with the big bang, a million eyeballs, that golden moment where a message reaches every heart, and the earth moves for everyone simultaneously. But in the new social media environment, we ridicule and mock big campaigns when they don’t make sense to us – and our voices are so loud brands can’t help but hear. Conversely, we cheer those that listen, move collaboratively, give us choices and help us make our mark. As Marcus Brown recently wrote marketers / social business people need to “watch and listen to all of the tiny noises, the personal moments, the little disasters and the massive moments of personal joy that surround us daily. We should be improvising with the tiny stories.”
  4. We likee, we buyee, and there’s no excuse for metrical ignorance: There are various studies showing correlation between liking and following brands, and propensity to recommend, purchase, and purchase more from them. (And stats showing that poor social media engagement impacts bottom lines.) That given, there is still no need for any marketer to settle for anecdotal or macro-data: from Facebook insights to Google goal setting, tracking the effectiveness of digital communications through the customer and stakeholder funnel, brand by brand, product by product, is a matter of effort and skill, not luck or magic. There is simply no need, with the wealth of metrics at our fingertips, to be asking rhetorically the value of social media activation versus broadcast placements.

According to a Comscore/Facebook survey Starbucks reaches more non-fans than fans organically through posts on its page… Starbucks are being seen by double the amount of people who are fans every time a post is shared. The same survey also reported that exposure to a Starbucks post resulted in 38% of people increasing store purchases. Ultimately engagement delivers to the bottom line too.

Chris J Reed / Comscore

Business Insider has shared a fascinating look at what helped the Obama campaign raise so much money during his recent successful presidential bid. The key was a highly successful combination of science and creativity – with what has been described as “strange, incessant, and weirdly over familiar” email subject lines and content.

A/B testing is a technique popular with web designers. It involves showing two different versions of a page to users – and measuring which gets the best response (this could be in terms of time spent on page, or the completion of a desired goal – i.e.  purchase or successful registration). The Obama campaign triumphed by being brave, cheeky, and optimising subject lines, content and formatting (with often as many as 18 variations) incessantly to find out what achieved the best results for its fundraising emails. In the end, the ‘winning’ email subject line was ‘I will be outspent’ – a rather passive aggressive line that obviously shook Obama supporters with their worst fear: that his opponent would spend more, and win the election on that basis.

This provides a strong reminder of how valuable access to data is, in running successful communications activity. Even if you are working agency-side, and somewhat removed from your client’s analytics – it is imperative to know what is working by getting access to as much data like this as possible from across their channels.

within five years social media will be the number two way to engage with customers (after face-to-face personal interaction). That’s a step in the right direction, but why wait five years? The internet will have changed all over again by then, and business is in danger of being left behind.

Richard Branson, via Global IBM CEO Study

Last weekend I took part in a Cambridge Festival of Ideas panel discussion on whether we are being ‘sold online’ alongside Michal Kosinski of Cambridge University, Professor Bill Dutton of the Oxford Internet Institute and Nick Pickles of Big Brother Watch.

During this I proposed that practitioners who deal with collecting, processing, analysing and sharing social media data can operate according to a simple principle, to weight privacy in favour of individuals, and transparency towards institutions. For indeed, such responsible data dealing is essential for attaining and retaining trust in 21st century institutions…


Delving further into what this means in practice I put forward the following framework, which can be used by marketers to clearly document and ask questions of social data usage:

Best Practice Data Dealers Recipe Card

Note: my recipe card is loosely based on Tony Benn’s five questions to power

“Movenbank just released its financial scoring system that allows users to monitor and understand their financial data in a whole new way. This innovative real-time financial credibility score combines data from shopping patterns, daily spending and social influence into a personalized ‘CREDscore.’ … As part of their services Movenbank will provide instant real-time feedback on spending, with personalized insights that affect behavior.

Nestor Bailley

Today I’ve been checking out Movenbank – in the context of social media data beginning to affect our financial statuses. The site / service is presented very much from the perspective that banks have been letting us down with the way they offer products and services, and make decisions about our credit scores, and loans, unfairly… taking this ‘out of our hands.’

Movenbank will, in contrast, develop a view of individuals based on personality, and behaviour, some of it determined by a ‘fun personality questionnaire that identifies your financial profile:’

It’s too early to judge Movenbank, and what overall, this financial services innovation will do for us. But I think it’s worth asking a few questions about the implications of tying up self-identified personality traits, social media data and shopping behaviour to our financial ‘CRED.’

How will it work? Will we get a better score from consistently buying sensible organic vegetables and pulses, rather than last minute flights to Biarritz or a gorgeous pair of Alexander McQueens? And why should we?

Alexander McQueen fall 2012 shoes

As I understand it credit scoring is determined by how much you have been earning, borrowing, and paying back. What do we really gain from adding social media and precise shopping activity into the mix? Will some with poor traditional credit scores be able to borrow more? Will some with good traditional credit scores, be marked down in CRED for a personality or behaviour that this new score deems dodgy in some way?

Seems to me many of our financial problems have been caused by too much credit, not too little… if this is another way of opening the gates for people deemed a ‘risk’ by other measures, to borrow… is it a step forward? And will it really be fairer for us to be financially scored on our Facebook likes, tweets, and late night impulse Amazon purchases? For our financial status to be based on what we buy, and who we are, or have constructed ourselves to be, as well as, or instead of, how much we spend, borrow and repay?

Vegetables image from Bread, Water, Salt, Oil


This blog is about utilizing and optimizing the social web for business, pleasure and social change

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