Google Attribution 360, improved campaign measurement

attribution 360 | DBi
Today we will discuss one of the heavyweights of this new suite: Google Attribution 360. Attribution 360 promises to be a turning point in digital marketing and become the tool that will help drive success of marketeers. Its aim is to help you evaluate the performance of different campaigns – both online and offline – and all contact points (when and where the ad appears, etc.) throughout the customer journey. In this way, advertisers can discover and identify the correlation between acquisition and media activity, such as television, or even external factors such as weather phenomena.   One of the main advantages of Attribution 360 is that it not only allows measurement through various channels, but also of different devices, obtaining a single multi-channel and multi-device funnel. The tool has an unlimited number of preliminary steps to conversion within 30 days compared to 4 steps now showing Google Analytics.   Strengths: Data visualization and analysis of “path to purchase”. Attribution 360 also takes into account the position of the channels in the path, rather than just the participation. It also offers a new powerful data visualisation capability that allows reporting on different channels and media, with the ability to propose create media and budgetary plans, all within the tool itself. The data-based attribution modelling in this tool means better investment decisions and deeper understanding of the real contribution (role and weight) of each of the channels in your digital strategy. Knowing what action opens the conversion cycle, what actions influence the user journey and what action closes the cycle facilitates analysis of all interactions en route, not simply attributing... Read more

Which countries really won at the Rio 2016 Olympics?

We posted a couple of weeks ago at the midway point of the Olympic Games 2016 with a slightly different view of who was winning the Olympics depending on what data points to you for comparison. So now the games are over, how did each country do? Medal haul: Similar to the last post, in terms of the haul, nothing has change. The US and the UK had record breaking years while China, although still in third had a bad year compared to previous games. (table based on a points system – Gold = 3, Silver = 2, Bronze = 1). Key points: – Size of population and economy might are clear determiners for large medal hauls – There is no country that has more than 25 medals that has less than 60m inhabitants – Out of the top 15 countries by medal haul, the only non-OECD countries are China and Russia (judged on GDP per capita). – The top 20 countries in terms of government expenditure represent 68% of all medals won. Proportion of Each Team to Win Medals: Two weeks ago North Korea, with a team of 35 managed to win seven medals, pulling ahead early on by a strong showing in weightlifting. That’s a whopping 20% of their athletes. They haven’t won anything since and as such they have been pushed down to fifth. The new kings are Azerbaijan, Ethiopia and the US. Azerbaijan and Ethiopia showing the importance of dominating a particular sport to push you up the standings. Azerbaijan with a good haul in wrestling and all of Ethiopia’s medals coming on the track.... Read more

Who’s really winning at the Olympics? – Update on the following post

Usain Bolt the 100m and 200m, Mo Farah takes the 5000 and 10,000, Michael Phelps to win…everything. Olympic results are predictable. Well that depends how you look at it. Everyone so far has been focussing on the medal haul of each country, but what does performance look like if we factor in a few more variables? At the halfway point of the games we’ve been playing around with some data to see which countries really have performed well in the games so far. You’ll be surprised at the results. THIS DATA IS AS OF AUGUST 16 2016 – Check then update we did at the end of the games Medal haul: In terms of just medals, things are quite predictable. You’ve all seen this table, the US way out in front, with the UK and China scrapping for second (table based on a points system – Gold = 3, Silver = 2, Bronze = 1). One thing we can say for sure looking at the medals table is: size matters. In order to have a large medal haul,  lets say over 25 medals in total, size of population and economy might are clearly a factor. There is no country that has more than 25 medals that has less than 60m inhabitants and out of the top 15 countries with, the only non-OECD countries are China and Russia (judged on GDP per capita). The top 20 countries in terms of government expenditure represent 68% of all medals won. Proportion of Each Team to Win Medals: What about the amount of medals compared to team size. North Korea, with a team of... Read more

DMP: Adobe Audience Manager QA with James Trudgian

Data Management Platforms (DMPs) represent the next generation of marketing technology solutions. Designed to sit at the heart of a current marketing stack, they de-duplicate, aggregate, and merge multiple sources of data – be it online, or offline – and combine them with an anonymous unique ID for each customer. This allows an organisation to have a holistic view of their customers’ interactions based on onsite behaviour, in-store and purchasing behaviour, and any other touchpoints where the user interacts with your brand. The real power of this is the DMP allows you to create in-depth segments with these different data sets that can then be pushed out across all your different activation and buying tools, including onsite targeting, CRM, ad-serving, etc. Today, we spent a few minutes discussing Adobe’s DMP, Adobe Audience Manager, with James Trudgian, the Head of Strategy, Data and Insight for EMEA at Adobe. Here’s the audio version: What business problems do DMPs solve? Organisations want to put customer experience at the heart of what they do, which means giving users a consistent experience that reflects their interaction whether that’s online, offline, or both. Digital data adds new complexities to how organisations deal with their users and the tendency is for organisations to deal with customers in silos and as individual devices, rather than as people with many devices, often not connecting the dots between different departments. This leads to inefficiencies and lost opportunities as you aren’t able to create an accurate picture of your customers or their needs. DMPs bring these disparate data sets into one place and create customer audiences across those silos... Read more

Sentiment Analysis with Twitter

twitter sentiment analysis img
Recently, I’ve been learning the basics of performing sentiment analysis on social media data with R. In particular, I used the TwitteR library – written and generously shared by Jeff Gentry – to pull tweets mentioning companies competing in the digital environment out of the twitter API, analyse their content using text mining methodologies, and plot their sentiment against each other. This method can be helpful to benchmark the perception people have of a company against its competitors, and to understand what specific things do people like and dislike about them. The best part if it is that it all can be done for free. The aim of this post it not to provide a comprehensive guide about how to perform sentiment analysis on Twitter data, but to explain step by step one of the simplest methods to do so, and be used as a starting point to develop a more advanced analysis in line with your company strategy. Most of the code for this article has been taken from the Mining Twitter for Airline Consumer Sentiment. Result So, what is the expected result of a “sentiment analysis”? We’ll start showing an example output of the analysis, and then we’ll present the details of the process and the code used to get it. Sentiment Graphs The first and more visual result is a series of histograms that show, for each company in the analysis, the number of tweets for each level of sentiment. The tweets with a score lower than 0 are considered negative, the ones with a score equal to 0 are neutral and the ones with a score 1 or higher are deemed positive: On the... Read more

Google Joins the Marketing Cloud War and Launches Google Analytics Suite 360

Launch of Google Analytics 360 Suite
Google has launched its much talked about unified platform for enterprise level users; the Google Analytics 360 Suite. This is a set of six tools designed to help marketers measure campaigns, collect data from various sources, and share insights for programatic and automated marketing. It’s well known throughout the industry that Google has been working on this suite for three years, and yesterday they finally informed us via an announcement on their official blog. That Google Audience Center was an open secret was underscored when it was featured in the recent Forrester Wave report prior to its release – a nod of recognition that whatever they do, it would be important on an industry wide level. The new suite ​​is another step forward towards the integration of Google’s measurement, data and optimisation capabilities and represents a serious alternative to its rivals and industry players in the marketing technology space, such as Adobe, Oracle and Salesforce. “The era of fractional attribution in programmatic marketing is here,” said Paul Muret, vice president of Display, Video Ads and Analytics. What does Google Analytics 360 offer? Here’s a breakdown of what Google is offering users of Google Analytics Suite 360. Four of the six products are brand new, and are in limited beta. Google Analytics 360: A new version of GA Premium promises better integration with multiple points of data, in addition to Google’s advertising products. Google Tag Manager 360 (beta): An improvement on their tag manager, which offers a more simplified way to gather information from your site, increases the accuracy of data and simplifies workflows. This is a stand-alone, paid for... Read more