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Turn Big Data into smart data
David Brennan, Admap, December 2013, pp. 34-36
This article argues that Big Data misses the large majority of human behaviour that occurs offline, and therefore conclusions drawn from Big Data must be limited.
This article argues that Big Data misses the large majority of human behaviour that occurs offline, and therefore conclusions drawn from Big Data must be limited. Additionally, data collected online misses the subtleties of context in complex human behaviour and decision making, meaning that it captures only a snapshot of a person's behaviour that may change quickly, rather than displaying a pattern. In order to turn Big Data into 'smart data' analysis needs to incorporate offline information collected through other research techniques.
Find the right social data
Amy Avery, Admap, October 2013 , pp. 40-41
This article discusses the problem of social listening tools which are unable to correctly analyse the human emotions expressed, how tools are developing to allow this to happen, and what value this kind of tool offers to brands wishing to understand campaign ROI.
This article discusses the problem of social listening tools which are unable to correctly analyse the human emotions expressed, how tools are developing to allow this to happen, and what value this kind of tool offers to brands wishing to understand campaign ROI. 'Red Data' is the idea of finding the most useful data available, therefore simplifying Big Data and generating understanding. Social listening tools have often incorrectly categorised social media exchanges or missed the subtleties of sentiment expressed. However, developments in this area will allow brands to better understand what discussion topics drive business, determine which messages matter, and measure the ROI of campaigns. They may also help brands understand how social conversations impact on them and to create an indicator to predict performance.
Can Big Data and creativity play in the same sandbox?
Briggs Davidson and Mark Fielding, Admap, September 2013, pp. 34-35
This article argues that data and creative teams should be increasingly intertwined to maximise the potential of Big Data, and offers some tips towards achieving this.
This article argues that data and creative teams should be increasingly intertwined to maximise the potential of Big Data, and offers some tips towards achieving this. Data has often been seen as a necessary evil by creatives, but when experts work together to gain insight from the data it can empower creative teams to take controlled risks. This article emphasises the need for data experts in marketing and the wider team to be comfortable with data. Data and creative teams should work together at every stage of a campaign to enable greater insight, innovation, and the small scale testing of ideas.
Big Data: P&G says thank you to moms
Ashish Williams, Gary Tan and Win Huang, Admap, September 2013, pp. 28-30
Using the example of P&G in China, this article argues that there are five key planning processes for applying Big Data techniques to media communications.
Using the example of P&G in China, this article argues that there are five key planning processes for applying Big Data techniques to media communications. Big Data can deliver enhanced insight, efficiency, integration and content that connects with target consumers. The key to success is turning insights into actions, requiring a range a data sources which enable optimisation and targeting of campaigns to key consumer groups.
Big Data: Cut through the noise
Nick Barthram, Admap, September 2013, pp. 32-33
This article cautions against Big Data's ability to generate 'spurious correlations' and proposes seven steps to help generate insight.
This article cautions against Big Data's ability to generate 'spurious correlations' and proposes seven steps to help generate insight. Large amounts of data increase marketers' chances of finding randomness masquerading as correlation, with this problem compounded by human tendency to see patterns where they do not exist and to hold confirmation bias. This article argues that marketers should be statistically numerate, selective over what data is analysed, and strictly maintain clear objectives. They should allow computers to process data to spot correlations, but then apply human understanding and analysis to determine if they are spurious. Hypotheses generation by Big Data should be tested either in a live setting or through other datasets. Insights should be continually tested and checked as in the world of Big Data, things can change quickly.
From flags to feedback – how Mars uses insights to drive growth
Geoffrey Precourt, Event Reports, ARF Audience Measurement, June 2013
The insights function at Mars has been on a transformative journey since 2005. At that point, the return on investment from its advertising fell below industry benchmarks.
The insights function at Mars has been on a transformative journey since 2005. At that point, the return on investment from its advertising fell below industry benchmarks. By 2012, however, the level of payback was significantly higher than the norm. A key contributor to this process was the formation of its Catalyst Group: a single, centralized unit that provides the analytical direction for the whole company. The main priorities of this division were bolstering the firm’s internal insights capabilities, as well as working with the right partners to boost its understanding of the entire ecosystem. As these efforts have made a positive impact on the bottom line, senior managers have bought into the process, creating a virtuous circle of development.
The four best (and worst) uses of market research
Taddy Hall, Nielsen, Newswire, April 2013
Opportunities for business growth lies in doing things differently, but organisations often focus on a few approaches which do not offer actionable insights.
Opportunities for business growth lies in doing things differently, but organisations often focus on a few approaches which do not offer actionable insights. This article suggests that market research should not just focus on what consumers currently like about products/services, but also on the things consumers find to be a 'nuisance'. Businesses should then innovate new products to meet this need. They should also consider reconfiguring or repositioning products to capture non-users.
Mythbuster: Ignoring the 'still' majority
Les Binet and Sarah Carter, Admap, April 2013, pp. 9-9
In their regular column, the authors question why the advertising and media industries insist on ignoring the 'silent majority'.
In their regular column, the authors question why the advertising and media industries insist on ignoring the 'silent majority'. They point out that advertising likes to focus on what is easy to see and measure. So while 90% of the marketing universe consists of behaviour that cannot be easily tracked, the industry focuses on the easy 10%. Binet's and Carter's advice when seeing a "headline percentage", subtract it from 100 and spend more time thinking about that, probably larger, percentage as that is where most of the real action is likely to be.
How can we make Big Data smart?
Colin Strong, Warc Exclusive, MAP: Measuring Advertising Performance, March 2013
This presentation posits that adding judicious use of market research to big data leads to "smart data".
This presentation posits that adding judicious use of market research to big data leads to "smart data". It sees big data, gathered by researchers from both proprietary and open sources, as representing an opportunity to gain deeper understanding of human behaviour. The rise of smart data can be seen in the emerging disciplines of cyber-psychology and computational sociology. Various smart data measures and metrics - specific to individuals, segments and social networks - are discussed.
Using the digital debate in real-time to drive insight-led strategy and execution
Oliver Harcourt and Flemming Madsen, Warc Exclusive, Next Generation Research, January 2013
In this presentation, Samsung describes its journey to build stronger brand desire. It needed a new approach to make a continuous, real-time loop between the digital debate and action.
In this presentation, Samsung describes its journey to build stronger brand desire. It needed a new approach to make a continuous, real-time loop between the digital debate and action. To accomplish this, it needed to find the right tool to tap into the online debate, identify influencers and move from listening to analysis and insight. To overcome implementation challenges, it needed to gain buy-in, analyse and communicate insights. This allowed the company to influence communications and business strategy with instant market feedback on how sentiment was driving brand perception.
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