So you’ve got a shiny new programmatic build, and want to know how it’s performing.
Monitoring indexation, traffic, conversions, rankings, there’s so much to look at so what should you focus on?
Let’s take a look into a few things you should be monitoring, and how to go about it.
- 1 Key metrics that can gauge performance
- 2 Breaking the metrics down
- 3 Tracking a programmatic build
- 4 So many metrics, so little time
Key metrics that can gauge performance
The key metrics you should be monitoring will change through the life cycle of your build.
A build that has just been launched, should have more emphasis on tracking indexation, rankings, and even impressions.
For existing builds, or as a build gets older, more emphasis should be placed on two other key metrics. Conversions & clicks.
Everything else is still important, particularly for understanding what modifications could be made to improve performance, but if your setup isn’t driving converting traffic, then what’s the point?
Unless you’re a build that’s purely advertisement reliant, of course.
The overall count of pages indexed. This can be monitored via the coverage report, and XML sitemaps.
Kind of an extension of indexed pages, ranked pages is the count of pages ranking in the top 100 for the most related keyword possible. You load up a rank tracker with keywords exactly matching specific pages, and then monitor them showing up in the top 100. It’s great for ensuring that Google is actually ranking the pages, albeit low to begin with, rather than just reporting they’re indexed.
Most will just use average rank for rank monitoring. Whilst it’s great, it’s unweighted. Keywords with 10 volume will have the same value as keywords with 10,000 volume. I prefer to use ‘estimated traffic‘, which takes into account both the ranking, and the search volume for a keyword, giving a much stronger indicator of ranking performance.
Clicks & Impressions
Pretty obvious here, but clicks & impressions are a clear indicator of performance. Can be broken down by keyword level (albeit filtered data) and URL level, it can give us quite a bit of drilled-in performance data.
Last, but certainly not least, conversions. Provided you’re not an ads-driven programmatic build, conversions should be the key of all key metrics. It’s the most direct indicator of the actual performance of the traffic. If it’s good traffic, it’ll convert. Bad traffic, won’t. Even a badly optimised conversion funnel will get traffic into the funnel. These conversions can be broken down into different levels, from funnel entry to funnel exist, ie add to cart verse purchase, to get even better data.
Breaking the metrics down
When analysing the performance of a programmatic build, you can’t look at it at a page level.
You’ll spend hours upon hours looking through the data.
You need to analyse it at the category/site section level. Grouped performance data essentially.
Look at the data for sets of the pages at once.
You could break the data out by category, sub-category, location, or even analyses like ‘location pages verse generic pages’.
Any way you feel it could be analysed that returns a smaller amount of overall groups.
Analyse keyword data by categories
You should group your keyword data into categories and view your performance at the category level. Aggregate all the performance data, and view key metrics like clicks, impressions, and estimated traffic performance by category.
Analyse traffic and performance data by site sections
Just like you group keywords into categories, you can use the same setup to categorise your landing pages into site sections.
A quick way to analyse site section performance from GSC data is to also group the landing pages into site sections in data studio.
Another trick here is to individually verify GSC properties of each site section. If you do that, you’ll get fully granular data for each site section, in its own property. Everything will be filtered to the site section.
Tracking a programmatic build
On top of the standard conversions/clicks, there are a few extra ways I look at performance, especially for a programmatic build.
As long as the GSC is verified before launch, analytics setup with conversions, and you have your rank tracking set up, you’re golden for launch. Everything else can be set up based on the historic data.
There are a few things you can start to look at after a launch, with some of the things I look at being below.
Identify top keyword templates and generate tracking keywords
You might be wanting to track thousands of keywords for the overall project, which is great, but sometimes it’s a bit of data overload.
Focussing on a small subset to gauge overall performance can really help you get a quick analysis done.
I recommend identifying your top keyword templates and then generating a subset of keywords for each main section. I personally track between 100 & 500 keywords per site section/page type.
So for the ‘buy’ channel of real estate, you’d have;
real estate for sale <location>
properties for sale <location>
and then ‘rent’ might have;
rental properties <location>
properties for rent <location>
Using these templates, pick the top 100 locations, or whatever the variable is, and generate the keywords. You could use merge words, or follow my guide here on bulk keyword generation.
Load these up in a rank tracker, in either different projects, or tagged separately, so that you can quickly view the overall group performance.
I use serprobot, and would set them up like;
Domain.com – Buy Keywords
Domain.com – Rent Keywords
So that I can view averages just on the dashboard, and quick view performance for that whole category.
You might also track a subset of generic verse property type keywords. Generic would be;
property for sale <location>
but then property types might be;
houses for sale <location>
apartments for sale <location>
And you could do a similar thing with generic vs location keywords.
Just follow the same process as above, and generate the keywords and then load these up in the tracking.
Monitor your indexation
During the initial phases of a build, monitoring indexation is a great way of understanding how Google is initially reacting to it.
Indexing is the first sign of happiness.
An indexed page means it’s passed the initial checks by Google, and they at least, somewhat, found enough value in the page to index it.
If you’ve never worked on a large-scale programmatic build, the amount of pages that don’t get passed the discovered/crawled stages sometimes is incredible. So passing this stage is a great first step.
You can do this through the coverage report at the top level, and by site section if you’ve verified the individual site sections in their own GSC property.
Another good method is creating site-section-based XML sitemaps. These can then be clicked in the sitemap report, and you can view the coverage report based on just the XML sitemap URLs.
The final method of initial is by keeping an eye on the keywords with a URL ranking in the top 100. These should generally be the most related page to the query, so just watching the quantities of keywords with a URL ranking, as a per cent, can give a good indication here too. It might be a bit more performance/quality related than direct indexing, but everyone knows it gets pretty junky after a few pages anyway, so even a shockingly optimised page could pop the top 100!
Count of URLs with impressions
Not so much a key metric, but another great view of performance, is monitoring the overall count of URLs with an impression.
A more ‘advanced’ method of monitoring indexation, keeping an eye on the count of URLs with impressions is a great way to monitor the overall performance growth across the entire build.
Somewhat useful at the start, and particularly great for self-expanding programmatic builds, this metric will help you confirm whether the wider system is driving the performance, or whether it’s a small subset of URLs that are performing the best.
It’s great for ongoing monitoring, especially when you start to break it down by sections and page types.
Analyse the per cent of live pages that are actually generating impressions.
So many metrics, so little time
Keeping what you’re tracking to a minimum, will help you avoid data overload.
Think about what metrics you can’t backdate, like ranking information, and ensure they’re all setup just in case you need them one day.
You never know what you’re gonna need, and when.