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Predictive analytics has been around for a while, as has machine learning, but it's only now with the profusion of cloud-based software in marketing that this form of data analysis has started to take off.
AgilOne is a US company, launched 2012, now branching into the UK, that provides predictive analytics software. I spoke to CMO Dominique Levin to find out more about this technology.
Is it powerful enough to make one-to-one marketing a possibility and not a fallacy?
At this year’s Digital Cream event in London we hosted a series of roundtables discussing big data and, more specifically, ‘data-driven marketing’ alongside senior marketers in the industry.
The three sessions gave us a fantastic opportunity to talk about key issues in big data as well as tackling both widespread and sector specific problems.
Big data is such a contentious issue these days, mostly down to the overuse in marketing headlines and sound-bites. However, there was a serious desire from all attendees at Digital Cream to get to the crux of how the big data landscape is shifting and how to survive it.
The overwhelming view was that big data cannot be ignored and proactive steps must be taken to remain competitive. The only problem was – how?
Data is a hot topic. It always has been. But now there’s way more of it.
For all those tired of the talk of big data, which is changing services, there’s also a backlash, a sort of arts and crafts movement in statistics (no offence intended) with a focus on using ecommerce product and customer data efficiently, now that it can be looked at it in high fidelity.
Perhaps the biggest boom area in marketing technology at the moment is CRM. But aside from companies getting their houses in order, building them on the rocks of data collection, triangulation and testing, there’s talk of a further revolution.
The revolution comes in the form of a data empowered consumer. The customer is gaining more awareness of and control over her data. Will we approach a point where consumers are fully aware of the value of their data, and are capitalising on it with companies that enable a value exchange, providing extra services, products or savings?
Well, this post is going to have a lot of rhetorical questions in it, questions inspired by last week's Personal Information Economy conference run by Ctrl-Shift. But it will also have some facts and a particularly good case study, Money Saving Expert’s Cheap Energy Club.
So, have a read and let me know how far you think a data empowered consumer can change advertising and marketing.
We are all sharing more data than ever before with other organisations in our emerging Big Data Society. Sharing lets us use our resources much more precisely and produce completely new services.
But misusing customer data risks destroying customer trust. Still, we all need that missing piece of the Big Data puzzle, so we all need to share more.
Last year Econsultancy published an article claiming that some businesses doubt the value of personalisation.
Although 94% of companies agree that personalisation ‘is critical to current and future success’ less than half of companies are personalising their website experience.
This isn’t because they think personalisation is unimportant, but because they don’t actually know how to make the most of it.
However, even the smallest of companies can target their consumers directly using personalised content.
The phrase of the day is 'Big Data', everyone talks about how it can boost your business and make you a successful organization.
But how can big data help a small business? Can you still use it to drive decisions and optimize your business?
The answer is: yes you can! In this post I will provide a few tips that can help SMBs to get up and running with data analytics.
Let me tell you, it's more than just the excellent doge.
Last year I started writing for the Econsultancy blog and it’s allowed me to go to a lot of cool conferences and learn about some new things, from Google Glass to big automated email and CRM systems.
Here are some of the things that stuck in my mind from last year and perhaps a few things you might not know about digital and the interweb.
For regular followers of our interweb anti-format post (crazy stuff from across the web), don’t worry, it will return next week.
Yesterday I was invited to the UK launch of a new personalised video platform, created by Dutch company Rednun.
Rednun claims that if you want the biggest impact possible for the maximum number of people, you can’t do it by producing just one video and uploading it on a shared video platform. You need to personally tailor each video for every individual viewer.
The user provides their personal information to a company, the company provides that database of customer information to a production company. The production company creates a video specifically for every customer, providing maximum relevance and complete personalisation.
Rednun claims the rewards are higher conversion rates, brand loyalty, visibility and engagement rates.
I'm naturally skeptical of most things, especially in terms of the technology needed to achieve mass personalisation and the above goals promised by the company, so here's a rundown of the presentation with a few of my own thoughts peppered throughout for balance.
In late 2012, Econsultancy published the latest edition of its Marketing Attribution Management Buyer’s Guide, at a time when attribution was a particularly hot topic for marketers.
Vendors were furiously marketing their attribution platforms, and there were blog posts galore on the subject. Since then, talking about attribution, particularly in the same breath as the dreaded term ‘big data’, appears to have gone somewhat off the boil.
Or so I thought, before attending a recent Econsultancy roundtable on the subject of marketing attribution, where discussion and debate was as lively as I have seen at a roundtable.
Advertising on the internet and mobile has increased by 17.5% to £3.04bn in the first half of 2013 according to the IAB, an increase of £607m compared to 2011.
Analytics has played a key role in this growth by helping marketers accurately measure return-on-investment (ROI) and justify reallocating traditional media budget to digital marketing. However, with the amount of data now available to digital marketers via analytics, they’re in danger of becoming data squirrels that hoard data but do nothing with it.
There aren’t enough analysts in the world or hours in the day to manually analyse all the available data, and crucially, turn it into actions which optimise revenue outcomes.
First off, what is it?
Well don’t let anyone tell you it’s down to sample size, or about measuring everything. It’s about combining datasets (sometimes ‘dirty’ ones), contrasting them in different ways, and doing it as quick as possible.
Sometimes this necessitates great computing power, but not always. You can read more about such technology as Hadoop and GreenPlum in this nice little article).
Datasets are multiplying as we measure lots more than we used to. This means our thinking has to broaden – no longer is ‘what can we do with our database of email addresses?’ the question, rather ‘what data can we look at to give us the best idea possible of a customer’s stage in the buying cycle and what they’ll be receptive to next?’
The definition of big data isn’t really important and one can get hung up on it. Much better to look at ‘new’ uses of data.
So, here’s some examples of new and possibly ‘big’ data use both online and off-.
Richard Branson’s Virgin empire incorporates a broad range of brands and companies that take in travel, TV, music and spaceships.
All these disparate businesses have their own websites, but the overall corporation is represented by Virgin.com.
This site has undergone a huge transformation in the past 10 years, morphing from a simple web portal into a content-rich site that aims to epitomise the Virgin brand experience.
At Econsultancy’s JUMP conference last week, which formed part of the Festival of Marketing, Virgin’s Bob Fear described how the site was redesigned by the content team working hand-in-hand with data scientists.
Fear’s team consists of journalists and writers, so the thought of working with big data appeared somewhat confounding at first.