Setting up a lead generation program in 5 Days: Day 4 – A/B Testing | Travel Research Online

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Setting up a lead generation program in 5 Days: Day 4 – A/B Testing

Often overlooked in the creation of a lead generation program is the need to test tactics to determine the most effective formats, copy and offers. Marketers refer to such testing as A/B Testing or “split testing” and it is a proven way to increase the results of your lead generation efforts.

In split testing, the tester will change a single variable in some aspect of an effort to see which variation better performs. So, for example, in an email campaign you might use two different subject lines and send one subject line to 5% of your list and the other subject line to another 5% of your list. Whichever subject line produces the most opens for your email offer you would then use to market to the 90% balance of your list.


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Testing takes time and is an intensive exercise. However, the results can be dramatic. It is important to vary only a single aspect between the two tests so you can clearly determine the cause of a performance improvement. A/B Testing pertains to almost any type of marketing effort including banner ad advertising, print ads, SEO and Key Word marketing and, of course, email campaigns.

Naturally in any given effort there are dozens of variables to test. The wording of an offer, landing pages, headlines, follow-up methodologies, pricing and even calls to action can all be modified and tested. Over time you can develop a set of best practices customized to your demographic and clientele.

Even the smallest of elements can be tested. For example, think about how your style your domain name in advertisements. Which works better:

www.travelresearchonline.com

or

www.TravelResearchOnline.com

The lesson is to continually test new aspects of your marketing efforts and then analyze the results with an eye to developing a set of best practices particular to your own particular marketing strategies and tactics.

HubSpot offers an excellent guide to A/B Testing.

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