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There are several approaches to conversion optimization with two main schools of thought prevailing in the last few years. One school is more focused on testing to discover the best way to increase website, campaign, or [[landing page]] conversion rates. The other school is focused on the pretesting stage of the optimization process.<ref>{{Cite book|last=McFarland|first=Colin|url=https://books.google.com/books?id=Z9B-7cHB5UwC|title=Experiment!: Website conversion rate optimization with A/B and multivariate testing|date=August 17, 2012|publisher=[[New Riders (publisher)|New Riders]]|isbn=9780133040081|___location=[[Berkeley, California]]|oclc=817741617|access-date=September 13, 2020|archive-date=May 7, 2021|archive-url=https://web.archive.org/web/20210507114802/https://books.google.com/books?id=Z9B-7cHB5UwC|url-status=live}}</ref> In this second approach, the optimization company will invest a considerable amount of time understanding the audience and then creating a targeted message that appeals to that particular audience. Only then would it be willing to deploy testing mechanisms to increase conversion rates.
== Calculation of conversion rate ==
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