Small Data - Low Hanging Fruit You Can Bank Today
posted by Stuart Cumming ~ 17/06/13
Category: Marketing
Tags: Data Strategy
There’s been a lot of talk about “Big Data” recently. Certainly mind-boggling to think that Walmart is producing an amount of data that would fill 60 million, 5-drawer filing cases every hour!

But as we sit and wrestle with how marketing budgets can be best spent to deliver spectacular ROI, it’s sometimes more about doing the most basic things well rather than introducing a new level of complexity.

And that’s why you may well want to start thinking about what I call “Small Data”.

But first a little bit of background…

For the past 20 years that I’ve been attending Direct Marketing Association (“DMA”) conferences in the US I’d been left with the impression that most US DMers had a level of data management that well, to be blunt, just made us Aussies look like their country-cousin hicks.

Use of multi-variable analysis was just about a given; test & measure, test & measure … I mean, why wouldn’t you?

At last year’s DMA Annual Conference in Las Vegas I thought I’d put that to the test. Well I was certainly surprised at what I found!

I attended a panel session that included a discussion with execs from two of the largest and well-known global data companies. One had just completed an in-depth study of their customers’ data quality.

(I’ll not name them because it doesn’t matter to this story and I’d like guys like these to continue to share their experiences candidly in those types of forums.)

After sitting there listening to their stories it occurred to me to ask them just how good their clients' data really was. Their response was, eyes downcast, "not great; name, address, email......"

So this lead me to think that for many SMEs the key issue might not be how to emulate Walmart’s data management, but more about getting the most out of what they already have.

So here are what I think are 6 examples of “Low Hanging Fruit” that you can start to implement today and bank from your next campaign.

1. Choose database software which best meets your needs. Excel spreadsheets are not databases and though a junior can probably work with them they are no substitute. Get familiar with the type of queries you can run so that as your expertise increases your software can deliver what you want.

2. Clean up obvious mistakes such as missing fields by running a report to identify them and then resolve the issues. If you are missing email addresses then an email capture campaign could be the answer. 

3. Age the records (because the more recent the purchase the more likely they are to purchase again) and run a reactivation campaign on the oldest. Those that fail (bounce or not respond) could either be deleted or put into a “Last Resort” list.

4. Segment into something strategically useful. A recent commercial real estate list we saw with 10,000 records had no information on the type of property the customer was interested in so everyone got the same listing of properties. A simple tagging could be the answer with fields such as Office, Warehouse, Showroom, Truck Access, Creative Space, etc.

5. Work the List. If a list isn't used regularly it can become stale. Why put all the effort into establishing and maintaining the list if you aren't going to do anything useful with it? Perhaps also look at affiliate marketing.

6. Analyse the data. Analysis doesn't need to be at Rocket Science level. Look at a sample of the data and see what patterns could be playing out. Take these patterns and apply them to a larger sample of the data to determine accuracy.

As you get more confident in your handling of the data you will start marketing more relevantly (and profitably!) not only to your existing customers but also to potential customers. 

I’m sure there are plenty of DM veterans out there whose own experiences have uncovered other examples that are just as easy to implement. Why not share them with us?
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