Technique - Banish DM rules to get the most from email marketing

Direct Response 26-May-06

Even though email marketing is still in its infancy, it is clear that it doesn't have to observe the same laws as traditional DM. It is flexible, cost effective and enables you to cast the net much wider, says Dan Bannister.

Whatever you know about mail targeting, put it to one side. The advent
of email means that direct marketers now have to look at targeting and
data in a completely new way, turning the old DM paradigm on its

head.

But, before we get into the nitty gritty of targeting, it's important to
remember that email marketing is all about making sure that emails are
delivered to the targets' inboxes. Imagine the uproar, for example, if a
sizeable portion of direct mail didn't reach homeowners'
letterboxes.

Yet this occasionally is the case with email marketing because either
the email broadcaster isn't able to deliver successfully (via lack of
agreements with ISPs such as AOL, MSN and Yahoo!) or because the
campaign creative contains wording that triggers an ISP's spam filter to
kick in.

So, before you even look at email targeting and email data, make sure
you look at the best ways of ensuring deliverability. Without this,
anti-spam filters may be more influential than either the data or
targeting, leaving your campaign to fall at the first hurdle. That said,
how do you target email?

Banish preconceptions

Direct mail is based on the idea that the more selective and narrowly
targeted a campaign, the better the return on investment (ROI) per pack
sent. A typical direct mail piece comprises design and copywriting
costs, paper costs, print costs, data costs, data processing costs,
fulfilment costs and postage costs. Direct mail campaign planning,
therefore, demands that target groups are picked as narrowly as possible
to maximise ROI.

Email costs, by comparison, are much lower. Apart from basic design and
copywriting, the only cost incurred is the data and email broadcast.
Therefore, email marketing may allow you to broaden your selections,
giving you a far bigger data universe and enabling you to target
individuals who, rather than being the "most likely" to buy your
product, might be individuals who "could" buy your product.

Above all, don't be afraid of being accused of "bad DM practice".
Remember that email campaigns aren't spam because every individual has
opted-in under EU law. Recipients have agreed to receive your email.

Widen your targeting criteria

If data and email broadcasts are the only real costs in email marketing,
you should be able to broaden your data selection to include any person
who is in the right age range and gender to buy your product.

Take, for example, a men's health vitamin product. In traditional DM you
might want to narrowly select fit and active adult males to keep costs
down. With email marketing, you can afford to email any male adult
because the only cost is the data and email broadcast. Why restrict it
to only fit and active adults? Indeed, you might find that no single
male target group has a biased preference for a healthy vitamin product,
and that response rates across all male groups provide a good ROI.

Broad data selections are normally cheaper to purchase than tightly
selected data groups, making wide selections even more cost effective
for your email campaign. Remember too that tightly selected lists will
soon become exhausted, leaving you with no possibility to purchase more
email records in the future.

Testing Options

When testing, use data segments of no less than 50,000. Just be aware
not to test for testing's sake and, while it is possible to test
campaign creative for each list by simply re-wording the headline or
copy and changing visuals on the email, bear in mind that testing
different creative executions will raise your campaign costs, so test
intelligently.

Email marketing is the perfect medium for testing because it delivers
results in real time, allowing you to roll out a successful test
immediately.

Just make sure you're ready if you need to scale up quickly.

Don't give up

Email campaigns are influenced by a huge variety of factors, many of
which are outside a marketer's control. If an email marketing campaign
has failed, employ a professional to examine all the possible reasons
why this might be the case. The professional will be able to identify
why your campaign fell short and make recommendations as to how you can
do better next time.

The rule book on email marketing hasn't been written yet, but it's in
the process of being written by people like you and me. Therefore,
banish preconceptions and don't be afraid to ignore many of the
traditional direct marketing rules.

For email, many of the old rules don't apply. Only astute marketers
realise this and it takes real courage to go against the DM grain and
implement a new paradigm. You'll find, however, that the results will
soon be worth it.

- Dan Bannister is director at Vivid Medianet.

CASE STUDY: PruHealth

PruHealth is a joint venture between Prudential UK and Discovery
Holdings, the South African private health insurer.

PruHealth's approach to health insurance is to offer reduced premiums to
customers who look after their health and offer large discounts with
many health and fitness partners.

PruHealth was not convinced by the high costs associated with purchasing
profiled email lists and wanted to promote its health insurance product
in a fresh and innovative way.

It looked at emailing a broad selection of the UK population rather than
focusing on narrowly selected data segments. The email's primary aim was
to raise brand awareness and drive interested parties to their call
centre for a personal quotation. Several million people have already
been emailed in 2006 and have been offered a health insurance product,
with the incentive of a gift for those who became signed up.

The successful campaign clearly showed that by buying data competitively
and targeting widely rather than in tight segments, email marketing can
deliver outstanding ROI.

Indeed, it confirmed the view that in email marketing, wide data
selections can often be preferable to narrowly selected data groupings.

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