Time Poor, Data Rich

I’ve been pulling together a piece to help empower planners at my agency to roll up their sleeves and get stuck in to doing their own insight gathering and analytics, rather than brief an analyst to do it for them.

When you line everything up it’s amazing what a modern day planner/researcher can get if they know where to look. I thought I’d share some of these tools here in the hope that someone out there might be able to add in some of their own.

Google’s Adplanner can tell you about site visitors, time spent and demographics (Google are a bit hazy on methodology, but they’re a clever bunch so let’s just play along). It can also allow you to create a bespoke audience based on sites they have visited, keywords used in search, etc, and then look at what other sites they visit (note, you need to sign in to Google to use it).

The daddy of web insight tools Google’s Insight for Search has been around a while. It’s a breeze to use and allows you to look at search trends for multiple terms by region and time. Top tip, combine it with their Adwords Keyword Tool to get actual search volumes.

Wordle has brought some much needed pizzazz to tag clouds. They just look so pretty. Paste in text from any doc, or try pasting in Tweets around a keyword (use this to find the tweets) to instantly visualise how a brand is being discussed.

Tag Galaxy must win the prize for visualisation. It crawls Flickr and grabs images tagged with your keyword before illustrating the results on a spinning interactive globe. Great for demonstrating the visual cohesion, or lack of, for a brand.

Brilliant new tools are also emerging from the likes of Facebook, Twitter, YouTube and other digital giants who are sitting on a ton of data. In time these will be as sophisticated and easy to use as the Google suite.

The most amazing thing though, is that all this is available to anyone, anywhere for absolutely nothing, zero, zilch.

Insight by Algorithm

With simple digital analytics you can quickly and easily paint a rich picture of your customer. Let’s say you’re Ford and you want to know about visitors to pages on your site featuring the S-Max MPV. A quick run might turn up the following:

Visitors to the S-Max pages also spend time on car sites such as What Car and Car magazine - maybe they are looking for some independent advice. They also over-index on sites such as AutoTrader - perhaps they want to see what prices are like for used Fords. Intriguingly they also score highly for food related sites - perhaps they are modern cosmopolitan types who love cooking as well as cars.

They usually arrived at the site from Google, but downstream they often went to social networks after leaving the Ford site - to talk to their friends about cars perhaps.

The analysis also shows that they are most likely to be ‘new homemakers’ - so maybe looking for a car to suit a young and growing family. You can also see that ‘new homemakers’ are likely to visit interior design sites such as Mydeco and Fired Earth.

So, a strategy built around young families with an interest in food, design and interiors, utilising social networks, looks like a great idea.

However, the following could also be true:

It’s true that visitors to the S-Max pages did also visit What Car and AutoTrader, but they couldn’t really give a stuff about food websites, that was their partner looking for recipes. People usually share the same PC at home and analytics can’t accurately tell different users apart. The downstream traffic to social networks wasn’t the potential S-Max buyers either, it was their 16 year old using Facebook.

And they are not what you would describe as ‘new homemakers’. They have two teenage children. Their interior design tips come from the Argos catalogue. But they do live near to a new housing estate and the geodemographics that link to the analytics assign all addresses in a postcode the same category.

In reality of course most of this noise comes out in the wash. But it does highlight the increasing amount of trust we place in algorithms to decipher the amount of media data we have to play with.