How to stop Google AdWords campaigns from failing

• Updated on: 2017-11-08
• Read original article here

Disruptive Advertising recently outlined the main reasons that AdWords campaigns succeed or fail, based on an audit of more than 2000 AdWords accounts.

They found the following causes of failure:

Looking at these reasons, it became clear to us that they all have one thing in common – they all stem from a business’ inability to understand the real value of each touchpoint in their customers’ path to purchase.

In other words, the AdWords campaigns that failed were not properly attributing the role of each keyword in the conversion path.

So, how do you prevent problems like this occurring?

Attribution is defined as the process of ‘accurately assigning value to each digital marketing touchpoint across the complete user journey, providing a great understanding of what combination of events drove conversions’.

Most ‘out-of-the-box’ models attribute a customers’ conversion to arbitrary metrics like the first or last step in their journey.

However, a data-driven, multi-channel attribution model uses unique, machine learning algorithms to consider each step in the journey in relation to the others. In doing so, it assigns the most accurate value to each touchpoint.

And how can attribution help with AdWords?

To answer this question, let’s take a look at the problems flagged by Disruptive Advertising, and see how a data-driven attribution model is instrumental in overcoming them.

Disruptive Advertising discovered that, of the 57.7% of AdWords accounts with conversion tracking, half had such a poor set up that they might as well not be tracking anything at all.

It shouldn’t come as much surprise that data-driven attribution can eliminate this problem for marketers. Attribution models work off a rich data set that is fed from a Customer Data Platform – which integrates all customer data sources, both online and offline, and across multiple sessions, devices and channels, into a single customer view.

This view provides granular visibility on the entire end-to-end customer journey. Working off this rich data source, attribution models are able to tell marketers exactly what is happening before and after a click.

A second finding for Disruptive Advertising was that the median conversion rate for an AdWords account was 2.18%. This demonstrates that, even though customers may be clicking on a keyword, this rarely results in a conversion.

Again, the solution can be found in accurate attribution – if you aren’t tracking your keywords properly, how can you know how many clicks are leading to conversions?

Proving this, Disruptive Advertising found that the top 10% of accurately tracked AdWords account had a conversion rate of at least 20%. Data-driven attribution modelling provides marketers with much-needed visibility of which keywords are contributing to conversions, and which are simply a drain on their budget.

The more money spent on search terms that don’t convert, the less effective your ad spend is. So how does data-driven attribution prevent this?

By nature of the fact this model looks at every single step in your customer journey, it is able to tell you exactly which individual keywords have resulted in 0, or next to 0, conversions. This insight is clearly invaluable to marketers who are trying to work out which keywords are bringing in a high ROI, and which are simply a waste of their money.

By figuring out which keywords are not increasing conversions, marketers can redistribute their spend in order to increase lead generation from keywords that are bringing in results, or those that have the potential to but have not been invested in.

Disruptive Advertising found that 61% of ad spend in their audit was wasted. When you consider the above scenario – where keyword bidding was optimized incorrectly – these results are hardly surprising.

And, as we already touched on, when you employ a data-driven attribution model to provide you with the much needed visibility of you keyword performance, it is incredibly simple to stop spending money on keywords that just aren’t bringing in customers, and to redistribute it to those that will.

From that quick overview, it is clear that the answer to ‘why do some AdWord campaigns fail’ is the fact that these AdWords account simply aren’t taking advantage of data-driven attribution.

By implementing this model, marketers can quickly gain a clearer understanding of exactly how their keyword campaigns are performing, and which ones are simply a waste of time and money.

Indeed, Fospha have seen a similar situation with one client with inefficient ad spend who, having employed a data-driven attribution model to reduce their wasted keyword spend, found that 50% of their keywords didn’t contribute to a conversion in any way. As a result, ROI was increased by 30%.

Click here to read the full case study on how Fospha enabled a client in online learning to make a success of its ad campaigns with a Customer Data Platform.

Content produced in partnership with Fospha. Views expressed in this article do not necessarily reflect the opinions of Search Engine Watch.