Although David Cameron famously denounced the incessant use of Twitter back in 2009 that hasn’t stopped the Oxford English Dictionary in including it into their new 2013 edition. Although the word “tweet” has been in the dictionary for years, it has only previously been included in relation to bird song. Now “tweet”, to post a [...]
What Historic PPC Spend Data Can Unearth
Ultimately a PPC campaign is only as effective as the amount of revenue it generates, whether directly through an ecommerce platform, via online leads or even through offline channels such as phone orders. It goes without saying, then, that a PPC campaign must generate more revenue than costs in order for it to be worthwhile for the advertiser.
Only when a PPC campaign has conversion tracking implemented can a true representation of its return on investment be calculated. This will give an indication of the overall revenue generated, whether as an actual figure or a relative one in terms of the value of a lead.
Why Historic Data is Important
Many advertisers get lucky with a PPC campaign – they add relevant keywords for their products, tailor their ads to generate healthy click-through rates, and find that their website does the rest of the work as the PPC campaign shuffles happily along, generating a healthy number of sales or leads, all the while its return on investment within acceptable levels for the business to remain profitable.
But even PPC campaigns that generate healthy profits require regular adjustment. In fact, healthy campaigns are exceptionally rife for optimisation so that revenue from historic sales is improved upon to drive future profits even further.
Mature campaigns are ideal candidates for improving future revenue. In the following example we’ll use an online children’s shoes store to see why.
Let’s imagine for a moment that a children’s shoes website has a particular ad group in its PPC campaign that targets children’s sandals. The total ad group spend for the year was £20,000, and the total revenue generated was £50,000: a total ROI of 150%. The revenue of each keyword exceeds its overall cost, and as far as the advertiser is concerned, this ad group is a keeper as the product remains profitable.
However, drilling down into the historic search terms reveals something interesting: the search term ‘children’s sandals’ accounted for nearly 30% of the total spend of this ad group, and yet it generated few, if any sales.
To put it bluntly, the website has spent £6000 on a keyword that led to no conversions! Drilling further down into the search terms reveals that only people who were searching for more specific types of children’s sandals – coloured, leather, buckled, etc – led to a profitable conversion. By filtering out this unwanted search term, the website can save itself £6000 per year, generating a potentially healthier ROI of 257% – a much more profitable figure. And of course, separate ad groups could also be set up to better control costs and visibility for the different types of sandals for which users have been searching.
Drawing upon such historic data gives you an insight into your demographic, as well as human behaviour. It might be that, historically, the keyword ‘children’s sandals’ is only profitable when it is positioned in lower search results. Perhaps people only committed to a purchase for this generic term between certain hours of the day. Delving even deeper into each search term using Google Analytics, it may be within a lengthy period of time certain keywords have consistently led to higher user engagement with your website, increasing the chances of a conversion being generated; the advertiser could therefore reduce bids on low-engagement keywords whilst increasing visibility on the high-engagement, low bounce-rate terms to promote conversions.
Whatever campaigns, ad groups or keywords are generating profits for your website, never forget the huge revenue potential hidden within the mass of historic data your visitors have created for you – it will allow you to spot patterns and learn more about your target demographic, whilst gaining a better understanding of how users behave with your website once they arrive there.
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