The Internet and Ecommerce have really taken off, especially in the last five years. By all accounts, this is going to continue. Recently though, there’s been much speculation about Internet growth rates and whether they and the revenues derived from them are really going to continue at such an astronomical rate.
The general consensus is no.
Verdict consultancy recently released a report (November 2009) that makes two predictions we need to be highly aware of:
1. Growth will become more difficult: Through a combination of factors such as a slowdown in broadband adoption and increasing maturity, there will be less new customers appearing online than in previous years.
2. Purchase process: Customers will shop around more before making their purchase, plus there will be more retailers to choose from.
Combining these factors will mean the traditional acquisition model used by a lot of current retailers will not be enough to meet their new targets. We can no longer just be on the hunt.
Most organisations are not farming
So what else can we do? Well a lot of retailers have started to farm their existing databases (customers) to try and get them to purchase more. It's far cheaper after all to convert a current customer again than bring on board an entirely new one.
This of course makes good sense. Unfortunately, the general approach is flawed and does release the much greater potential that skilful farming can provide. Very often the approach is centred around bulk email to a customer database with several offers on the email. We have no idea whether the customer will like the offer presented to them. It’s a simple numbers game – i.e. – if we throw enough email at customers, some of it will convert to orders.
Generally this has worked for retailers and has therefore earned email marketing the reputation is deserves of being a low cost delivery mechanism with high (if gradually eroding) returns.
This is not farming and it’s not hunting. It’s looking at your land and using a giant cannon to fire nutrients at your land. You have no idea which land grows what but let’s just do it anyway.
How to farm
So, having said all of this, what is farming? Farming is caring for your land (customers) and giving them the right food and nutrients to create the right results. So let’s drop the metaphor – it’s about highly-targeted, well-delivered messages based not only on the customer as a person but on their known behaviour.
Clean
To create an effective farming strategy, we first of all need clean data. Your database is probably not clean. In fact, it’s probably a mess. It’s been added to over time, not used very much or maintained, and could be in multiple places and with different types of data. We need to:
o Bring all of the different data sources together
o De-duplicate this information to have one single set of data per person
o In the case of email data, check that all the domains exist and can accept email and all email addresses are in the correct format
Now our data is quite clean, but we still don’t know whether the actual email addresses exist as this is a problematic area. Therefore our first send will clear out a lot of dead addresses. If you have already been sending regular emails, much of this will already have been done.
Segment
This is the crucial stage. Currently we have a mass of data that still can’t be used for farming. So we need to create smaller groups of data based on their preferences and behaviour. We’ll take an ecommerce site as an example. In this case you should have the following information:
o Who they are (contact details, name etc)
o Where they are (address information)
o What they have bought (purchase history)
o What they have returned (surprisingly important)
o When they buy (time of day, week, month, year)
o What they have responded to before (email activity history)
o Where they came from (original source of customer)
The list above is by no means exhaustive and you may not have access to all of the data, but it will serve well for our example.
Based on the data above, we need to find the groups of customers where correlations can be observed. For instance are a high percentage of your customers in the South East? Do people who are in the North only buy certain products from you and not others? Do people generally seem to buy in the evening, weekends or is there no pattern? All of these types of questions will help you identify pockets of highly concentrated data that share behaviour.
Target
Finally the action part – once we have identified some great pockets of data we need to use their behaviour to send them the right message, at the right time.
Let’s say we have 1,200 customers who seem to buy at the weekend, are located in the West Midlands and really like the electronics section of your website. That’s pretty specific, and sometimes it’s not always possible to get that specific but we can always try. We should segment as deeply as possible.
So we have the data, what can we send? Well the idea would be to send an email, possibly on a Friday afternoon or a Saturday morning or even a Sunday morning (all at points in the weekend) with an electronics-specific offer. If there’s something massive happening in the West Midlands that weekend, like strong gales or heavy rain, the campaign could focus on that.
Conclusion
Yes, it’s a lot of work, and it’s worth the effort. The returns that can be gathered from highly specific campaigns sent to well segmented data are much more than the returns of bulk mail shots scattered out. The hard work is also in the initial clean and segmentation. Following this process you should tweak, change and retest segments every so often (six months or so) but generally it’s just coming up with the right messages to send to your segments.
So please, start farming as well as hunting. If I get another email inviting me to a women-only networking event, I think I'll scream.
Rob Smith
Digital Director Blueleaf
