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ESV Digital

The secret sauce of successful paid digital marketing

By Steve Plimmer, ESV Digital

Marketing as a whole has some core prerequisites to be successful (measurable goals, a united and clear message to convey, smart budgeting). Paid Digital Marketing is no different but a unique strength of the digital space is a central factor in making all forms of digital advertising work. It’s not keywords, it’s not bids, it’s not directly being able to track and attribute conversions – for the latter, many advertisers don’t care about conversions so much. It is audiences.

Audience tracking, targeting and managing is Paid Digital Marketing’s secret sauce

There are certainly those who may claim the website is the real common denominator but you can have the best website in the world; if the users visiting it are low quality (poor intent, the wrong type of user in any way) it can’t get you results.

It is true that below-par websites will generally perform poorly but they’ll perform far above their fighting weight with good audience strategy.

Many advertisers are starting to get to grips with this fact, as PPC Keywords get diluted and many forms of control on search, shopping and display recede, because the biggest remaining lever of control (and insight) that seems to be surviving all this change is audiences.

What do we mean by audiences?

When speaking about audiences, I’m referring to literally any aspect of a user’s profile or behaviour that can be categorised, measured and targeted. This can include:

  • Location
  • Device
  • New or returning visitor
  • Prospective or returning customer
  • Engagement behaviour with the site or ads (e.g. video ads)
  • Age
  • Gender
  • Life stage/event
  • Content topics of interest
  • Occupation

This is by no means an exhaustive list and these are all beyond the basic audience segment of those who search on a search engine and self-select to be an audience member of “people who searched for product x.”

Many of these have long been used by Facebook advertisers or on LinkedIn but now marketers have a host of powerful options on both Google and Bing Ads plus other Display networks.

Uses

What is the value and what are the potential applications for all these audiences? Before anything else, you need to look at the data you have pertaining to these audience types. Without this we cannot know if it’s salient to even do anything with age groups, for instance. Maybe all ages convert about the same rate. And don’t forget to review how they may impact your CLV (Customer Lifetime Value).

To gather data about audiences that are not sourced internally, you can sometimes just run a report with these segments – normally the most generic user properties, like demographics or location – but for the more advanced and granular audience types, you may be able to add those audiences as “observed” audiences for a time to gather data. Google Ads is a great example of this. Once you have allowed time to pass and the data to accumulate, you may be surprised by some audience correlations and conversions on your site.

Once you have an idea of where performance opportunities lie, you can then decide how to segment targeting, auto-bidding and messaging to address them.

Not all audience uses must be hard-data-led, however. They can also be used simply to segment messaging. Decide what USP of your offering will ring bells with a certain audience (or layered audience) but also position the brand and set an appropriate call-to-action, imagery etc. In addition, you can identify your core target audience per your business plan and shape your strategy, in part, that way. If nothing else, it’s a good way to focus your budget on the user profiles through which you fundamentally want to gain market share.

You can leverage your CRM data to segment existing customers in a limitless number of ways and target them (subject to audience size) in PPC and Facebook/Instagram.

An extra bonus of the latter is that some platforms can take your audience and make look-a-like audiences to expand your penetration of people similar to those who convert on your site. You can take this further by buying email address lists of curated people and upload them as customer match lists.

Conclusion

When you come to choosing digital marketing platforms to use, ask yourself (and the platform in question) what audience targeting features it offers. Then ensure audience segmenting, messaging and management is core to your digital marketing strategy. This may involve many internal stakeholders and partners to do it right (web development, app development, data warehouses, data analysis, CRM teams and so on) but without making efforts to leverage audiences your competitors are going to eventually eat your lunch.

For more information about ESV Digital’s search marketing strategy, get in touch. You can also follow us on Twitter and Facebook for the latest updates.

Google Analytics Segments Vs Filters

By Ben Johnston – Head of SEO & Data Analytics – ESV Digital

Learn the difference between Google Analytics segments and filters, what they are, how they work and when you would use each of them...

One of the most common questions I’m asked about Google Analytics is the difference between a segment and a filter and the main use case of each of them. I’m often asked why you would ever use a filter when a segment does the same job and vice versa.

In today’s post, I’m going to briefly run you through what segments and filters are, how they work and the reasons for using each of them.

WHAT IS A GOOGLE ANALYTICS SEGMENT?

A segment in Google Analytics lets you view your metrics based upon specific criteria, for example only organic or paid traffic. They allow you to change your data on the fly and you use the whole of the Google Analytics interface just focusing on that data and, crucially, they do not change your data the way a filter does.

A segment can be applied retroactively, so you can see how your organic performance was last year and so on, and you can also create your own segments based on certain specific conditions. You can even share those custom segments with other Google Analytics users.

You can apply a segment to your Google Analytics like so:

Click the Add Segment button and you’ll see the list of pre-configured ones. As you can see, there’s a lot to play with and with the ability to import new segments from the Google Analytics gallery and create your own, there’s plenty of flexibility there to investigate your data from a variety of perspectives.

Segments are great and an essential part of your Google Analytics arsenal, but they’re not without their weaknesses.

Weaknesses Of Segments

As handy as it is being able to alter your data on the fly, there is inherently some lost functionality compared to filters. Firstly, there is less flexibility in what you can do with a segment than a filter – you cannot exclude a specific IP address or series of IP addresses with a segment, for example.

They also have a habit of triggering sampling within Google Analytics, where the data shown in a report is less than 100% accurate. If your dataset is small, you should be OK, but segments do bring this on much sooner.

WHAT IS A GOOGLE ANALYTICS FILTER?

A filter is applied to a Google Analytics view and permanently changes the way that the data is collected for that view, rather than changing the way it’s reported on the fly. Unlike a segment, a filter will not change your data retroactively.

Filters offer a great deal more functionality than segments – as well as just replicating the capacities of segments, which would be prudent if you have a high amount of traffic, you can also make sweeping changes to the way your data is collected, processed and reported. You can use a filter to rewrite the URLs in your page reports, for example, or to double-check the hostname or simply to exclude a section of traffic which you know is not relevant (your own team, for example, or bots). You can also unleash the power of regular expressions to really take control of your data.

Filters are a far more powerful solution than segments, but they don’t offer the same flexibility. You would use a filter for a specific task within a reporting view (excluding your own office’s traffic, for example), rather than using it to check the performance of a specific metric in most cases.

Weaknesses Of Filters

With the power of filters comes responsibility in their use. They permanently change the data in a view from the moment they’re applied to the moment you remove it. There’s no going back. They also can’t be applied retroactively in the same way a segment can. It’s this permanence, plus the additional Google Analytics knowledge required to set up a filter that is the key weakness of them.

In line with best practice, you should always have a completely unfiltered “All Website Data” view, to ensure data continuity and to use for checking that your data is coming through properly. You should then have other filtered views depending on the kind of requirements your site has.

At the very least, we suggest having the All Website Data view and a view which filters out your own IP address and the IP address of any partner agencies/ other offices etc, although we would typically go much deeper than this with a Google Analytics setup.

WHEN TO USE SEGMENTS & FILTERS

A segment is the best way to isolate a certain metric, channel or device in your reporting view and apply that to your historic data. If you want to see how many people have come to your site over the last three years from Facebook on their tablets, a segment is the way to go.

If you need to permanently change the way your data is collected, such as excluding your IP address, removing bots, or rewriting your URLs so that they’re easier to read in reports, you’ll be looking for a filter.

The key thing to understand about filters vs segments is that there is really no “vs” at all. They’re different tools for different tasks and a good setup uses them together. For most reports, you’ll be relying on segments to isolate and highlight different metrics, but to ensure that your data is as clean as it can be, you’re going to need filters to be involved.

Unsure of how well your Google Analytics setup stands up to best practice? Get in touch with ESV Digital and let us see what we can do to help. Follow us on Facebook and Twitter for the latest updates.