Tag Archives: data analytics

Western Europe leads the way in adopting new media

Western European nations are leading the way in the adoption of new media technology, according to a new study by ZenithOptimedia. In its New Media Forecasts report, ZenithOptimedia found that the leading country in 2012 terms of new media adoption was Norway, with an average penetration rate of 38.8% across three key digital technologies – smartphones, tablets and IPTV.

It was followed by France on 35.7%, the Netherlands on 35.1%, Sweden on 31.3% and Denmark on 31.2%. However, balance will shift a little towards 2015. ZenithOptimedia expects the Netherlands to be on top in 2015 with a penetration of 65.1%, followed by France 60.8% and Ireland 50.2%.

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Insight into Insights

If there was an ‘Insight’ Facebook page, it would have millions of Likes. Why have some marketers latched onto this concept tighter than a terrier with a new toy? This article explains what an insight is, why insights are essential to developing a competitive advantage, and a best practice for finding valuable customer and market insights.

What is an Insight?
Kieron Monahan of Arnold Worldwide offered one of the best definitions for insight that I’ve ever heard:

a surprising truth that makes you think again.

Insights are more than an observation; they are a discovery gleaned from the data and facts we collect. Insights serve a variety of purposes from sparking the innovation of new products to driving the delivery of a better customer experience.  Read More…

Using Attribution to Understand Content Impact on Customer Behavior

As we create more content, marketers are trying to understand the role this content plays in the buying process and which components have the greatest impact on generating conversation, consideration and ultimately consumption. So it’s no surprise that marketers are trying to understand how to leverage both marketing mix attribution and optimization models. Recently we’ve been receiving a number of questions about fractional and last-touch attribution. So we thought a brief tutorial on the topic of optimization and attribution modeling might be helpful.

There are a number of sources and tools available today to help create either model. Both attribution and optimization modeling are about improving mix and understanding the impact of marketing investments on customer behavior. Let’s begin by reviewing what these models are, when to use them, and how they are different.

Optimization Needs Attribution
Optimization relies on predictive models that track non-linear relationships between specific goals and spend levels in order to ‘predict’ the incremental changes in conversions based on the relationship between the variables. Many organizations attempt to ‘optimize’ campaigns via A/B testing, a form of scenario analysis. Unfortunately A/B testing doesn’t address the complex non-linear interactions. An algorithmic approach that simultaneously analyzes all possible scenarios is needed to see which combinations produce the best incremental results.

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CEOs Say Actionable Customer Insights are Critical

IBM recently published the 2012 IBM CEO Study Leading Through Connections. This study was based on face-to-face conversations with more than 1,700 chief executive officers and public sector leaders based in 64 countries around the world. The objective of the study was to gauge the perspective of CEOs and public sector leaders on emerging trends and issues. IBM has conducted this study every two years since 2004.

In the 2012 study, CEOs identified technology as the most important external factor that will impact their organization over the next three to five years. Just as important, it appears that CEOs are changing their opinions about technology’s primary role in the organization. IBM says the view that technology is primarily a driver of efficiency is outdated and that CEOs now believe the most important role of technology is to enable collaboration and relationships – between an enterprise and its customers, business partners, and employees, and among those same stakeholders. Read More…

Four Parameters for Selecting Marketing Metrics that Matter

With the increased pressure on business leaders to be more personally accountable for the performance and conduct of their organizations, the emphasis on performance management has trickled down and across the organization, including marketing. Performance management focuses on optimizing individual or group performance in order to achieve the organization’s key initiatives and objectives. Performance management includes the metrics and the data, measurement, alignment and analytical processes, methodologies, capabilities and systems needed to manage the performance of an organization. A sound marketing performance management process is essential for enabling marketing professionals to demonstrate and communicate marketing’s impact on and contributions to the organization.

Marketing measurement provides the process for being able to measure marketing performance. When we wrote our second book, Measure What Matters: Reconnecting Marketing to Business Goals, we emphasized that just because we can measure something doesn’t mean that it matters. Since the book’s debut in 2004, the content that marketing can measure has only proliferated. Focusing on metrics that are easy may give Marketing interesting things to report, but may not help us demonstrate our value, foster better decisions or enable course corrections. The whole point of performance management, marketing accountability and marketing measurement is to help Marketing optimize performance and achieve meaningful business results. Read More…

How to Make Data Interesting

Data in all shapes and sizes plays a huge role in today’s business environment. Whether it are the results from the latest viral campaign, the activity on various social media accounts, or complicated financial stats and graphs, we are all forced to deal with data on an almost daily basis. So why not spice them up a little?

This video gives a few questions to consider when processing raw data for reports and presentations and the like. It also gives a few tips and tricks to make your data visually attractive. That way, next time you give a presentation, your colleagues probably won’t use the COMA app on you.
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Whitepaper: The Social Consumer Brand Compatibility Model

Five years ago, not everybody could have foreseen the huge role social media would play in marketing today. Today, almost any brand realizes the importance of social media and either has or is working on a social media strategy. Some brands were among the early adopters and have taken a head start in social marketing, while others are still trying to figure out the best way to incorporate social into the marketing mix.

But social media are not like traditional media and require a different approach from a marketing point of view. It’s inherently interactive, and ever-evolving. Social media is more than ever about the relationship between customer and brand. This does not only take a different kind of communication, but also a different kind of data analytics. Social media are a potential source of a wealth of consumer information, but the question on everybody’s mind these days is how to get the best information from this vast pool of data.

The CMO Council report ‘The Social consumer Brand Compatibility Model‘ introduces a new way of analyzing social media data:

Social Consumer Brand Compatibility modeling is an emerging area of marketing science that seeks to navigate the mountain of social media data and take-away insights regarding customers and their interests. By analyzing posts, ‘likes’, and rich media content sources from Facebook, Twitter, YouTube, and other social networks, brands can glean richer information about media consumption, psycho-graphic, lifestyle, and personal interests. [...] Social data delivers heightened insight, allowing marketers to improve media selection and buying, as well as the relevance, resonance, and response of ad and promotional buying.

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SAS Customer Intelligence: Find Growth

‘So what do your customers want? Simple. They want what they want, when they want it, and however is most convenient for them.’

That’s easier said than done. Understanding and analyzing customer behaviour requires some heavy-duty data analysis, according to this vendor video by SAS. The first of a series of three on their Customer Intelligence solution, this video focuses on growth opportunities through the analysis of marketing and customer data. Because: ’in an age of increased marketing accountablity, it is not only ciritical that you act with speed and precision, but forecast accurate profitable growth across everything you do.’

If you know what the customer does, you can more accurately predict what they want, and where to utilize your marketing assets. While it’s only part of Marketing Operations, it’s not a bad idea to take the customer’s behaviour and preferences as a starting point for your marketing activity and business growth.

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Big Data Promises Marketers Big Insights

The amount of data being generated is expanding at rapid logarithmic rates. Every day, customers and consumers are creating quintillions of bytes of data due to the growing number of customer contact channels. Some sources suggest that 90% of the world’s customer data has been created and stored since 2010. The vast majority of this data is unstructured data.

It is not surpring, then, that study after study shows that the majority of marketers struggle with mining and analyzing this data in order to derive valuable insights and actionable intelligence. A recent report by EMC found that only 38% of business intelligence analysts and data scientists strongly agree that their company uses data to learn more about customers. As marketers we need to learn how to leverage and optimize this flood of data and incorporate it into customer models we can use to predict what customers want. Read More…

P&G Seeks ‘One-on-One’ Relationship with Consumers

Procter & Gamble, the FMCG giant, is using digital tools to build a ‘one-on-one’ relationship with shoppers, within a wider effort to enhance its marketing and innovation capabilities.

“With digital technology, it’s now possible to have a one-on-one relationship with every consumer in the world. The more intimate the relationship, the more indispensable it becomes,” Bob McDonald, P&G’s CEO, told McKinsey. ‘We want to be the company that creates those indispensable relationships with our brands, and digital technology enables this.’

One way the firm is exploiting such opportunities is via its ‘Consumer Pulse’ system, which analyses online comments. Comments are grouped by brand and delivered to a relevant individual staff member.

Broader initiatives include letting staff use iPads to download precise, up-to-the-minute insights about the production process, alongside equally rigorous systems covering transport and logistics, and automated retail ordering platforms for retailers.

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