Measuring what matters: Value vs Vanity. by Adam Kensington, Content Strategist

So you’ve taken the plunge. You’ve invested in a new website, created a new bit of content, paid for some Google Ads – now it’s time to sit back and watch the business roll in, right? 

It would be lovely if it was that easy. Digital marketing, after all, promises to get your name to the right people at the right time and in the right way, so why wouldn’t it result in more brand loyalty and new customers banging on your door?

The truth is it most certainly can, but it needs to be underpinned by a solid measurement framework that helps you adapt your tactics and tweak your strategy over time. There are hundreds if not thousands of metrics that can help you figure out what’s working and what’s not. So where do you start?

Value vs Vanity – what’s important to you?

Firstly, and perhaps most obviously, it’s important to work out what you want to measure and why. If your marketing is aimed at generating revenue for instance, it’s important to understand the difference between vanity and value metrics. 

“Social media likes” or “brand awareness” are NOT key performance indicators. They are vague and sometimes unhelpful indicators that don’t necessarily correlate to ROI and can skew your understanding of marketing effectiveness. 

Here is a brief look at how metrics can be categorized when analysing and reporting marketing ROI:

Vanity

• Website traffic
• Time on site
• Keyword rankings 
• Bounce rates
• Social media followers
• Ad impressions
• Page views

Value

• eBook downloads
• Conversion rates
• Phone calls into a business from prospects
• Marketing-qualified leads
• Customer acquisition costs
• Customer lifetime value
• Annual Recurring Revenue (ARR)

Vanity metrics aren’t completely invalid – they can be useful when qualifying a value metric. For example you might want to see specific page views increase with a goal of higher conversion rates. 

So in this instance the KPI might look like this: we want to see 1000 views of a web page that result in 100 eBook downloads. Of those downloaders, we want to see 10 sign up for a demo of our product and we want two to become paying customers with a combined ARR of £20,000. 

Now you’ve got a KPI that is SMART (Specific Measurable Achievable Realistic and Timely), the question is how you measure it. 

Campaign Measurement Tools.

There are many great campaign measurement tools available – the trick is to harness the power of each one to build a detailed picture of how each marketing channel is contributing to ROI. 

Google Analytics 4

Google Analytics is the industry standard for measuring website performance. GA4 was officially released in October 2020 and has shifted its focus in its measurement model. In previous versions, this was based on page views and sessions but it is now based on events and parameters.

GA4 has got the “enhanced measurement” feature built-in which allows automatic tracking for certain types of events (like scroll tracking, video tracking, exit tracking, site search tracking etc,) without any additional coding.

You can assign events a currency value which can help you see where commercial value lies in your attribution model (more on that later). So in our example you might want to set downloading an eBook as a micro-conversion (an action that does not have a commercial impact but may later through effective nurturing). 

Macro-conversions can also be created. These are higher, intent driven actions that lead directly to commercial value. So in our example a demo request would be directly linking a prospect to a sales person, pushing them further through the conversion funnel. 

To learn more about GA4 and to get started today, watch this quick video by Loves Data. 

https://www.youtube.com/watch?v=iJyGEuiIjOk

Google Tag Manager

Another part of Google’s analytics suite is Tag Manager. One of Tag Manager’s features allows you to assign marketing campaigns parameters that show how a conversion has happened. It uses UTMs (Urchin Tracking Module) on links (URLs) that are used in your campaigns. 

Taking our example, you might be running a lead generation campaign including content published on LinkedIn. You want to see how many of the new leads from a campaign originated from LinkedIn as the source, and the specific page that the lead navigated to. The URL you use for the LinkedIn element of the campaign will look something like this:

https://yoursite.com/blog/10-easy-ways-to-market-to-B2B-companies/utm_source=linkedin&utm_medium=blog&utm_campaign=winter2021promotion

UTMs have a number of parameters which have different uses. Here are the main ones:

Source – the platform or vendor where the traffic originates from. In our example LinkedIn but it could easily be your email newsletter

Medium – you can use this to identify the medium that was used to bring the traffic to your site. So in our example content on our blog but it could just as easily be social media, cost per click or an affiliate. 

Name – this is just to identify your campaign. In our example we’ve got a specific seasonal campaign called winter2021promotion

Content – this is more useful for tracking emails where you have two Call To Action links or a post with multiple links where you want to track which link was clicked, or when you’re A/B testing ads. 

Term – you’ll use this mainly for tracking keywords during a paid Adwords campaign, You can also use it in your display ad campaigns to identify aspects of your audience. 

One word of warning when using UTMs though. They are stubborn entities that stick to your links even when you switch to different networks and mediums. For example if a visitor picked your UTM enhanced link from Twitter to share on LinkedIn, it would still count as a share from Twitter. 

Advertising platforms.

Advertising networks like LinkedIn also include their own metrics that can be useful when evaluating the effectiveness of an ad campaign. Granular data that’s important to look at are Cost per Click and Cost per Lead. This gives quantitative data that can be useful but doesn’t reveal the quality of the lead itself. 

With applications like Google Adwords, you can track the all important Click Through Rates (CTR) and use events in GA4 to calculate the Cost Per Conversion (CPC) to help your bidding strategy. Whilst you might have excellent CTR of say 4% but are seeing a low number of conversions on a given page, the indication is that you need to make some amends to the landing page in order to funnel your users more effectively. 

It may be that your campaign copy or content isn’t leading enough, is too heavy, or the call to action may be situated in the wrong place. Other tools like Hotjar can be used to see specific user actions on a destination page and help you identify and optimise user journeys. 

CRMs

Customer Relationship Management (CRM) tools are now so advanced that they can track lead quality and automatically lead score your prospects – allowing your sales team to focus their attention more intelligently. 

Tools like HubSpot have marketing and sales automation at their core. They can dynamically group leads by behavioural attributes, improving the likelihood of conversion.

For example, if someone views three high-value pages on your website, has a high open rate of an email or regularly interacts with you on social media, you can assign them positive scores to quantify the strength of your digital relationship. You can then filter and sort your contacts based on their lead score and carve out custom campaigns.

Custom dashboards and reporting can be set up to help you evaluate campaign effectiveness. For example, you can set up a report that shows Twitter against LinkedIn CTRs revealing which channels are more effective per campaign. The advantage of this being stored in your CRM is that it can show a complete acquisition story from first sight right through to becoming a paid up customer. 

Attribution Reporting.

It is often said that prospects take seven touches to convert from a visitor into a buyer. It’s highly unlikely that someone will want to buy your product or use your service after just one exposure to your brand, which is why you use multiple methods of communication. 

Organisations like yours need to show ALL the interactions a customer took in their journey to provide attributable value back to marketing.  Moreover, it would be handy to have this all in one report. 

CRMs like HubSpot connect marketing campaigns with closed-won deals making this possible. 

There are a series of established attribution models that can be used to identify where you want to load significance in the sales journey. Here are a few examples:

First interaction  – attributes 100% of the deal revenue credits to the contact’s first interaction in the conversion path

Last interaction – like first interaction but instead attributing 100% of the deal revenue credits to the last interaction

Full path – attributes 22.55% of the deal revenue credits to the first interaction, lead creation, deal creation and last interaction each and then attributes the remaining 10% to all other interactions equally.

Linear – attributes the deal revenue credits to each interaction in the conversion path

U-Shaped – attributes 40% if the deal revenue credits to the first interaction and lead conversion interactions each and then attributes 20% to all other interactions.

W-Shaped – attributes 30% of the deal revenue credits to the first interaction, lead conversion interaction and deal creation interaction each, then attributes the remaining 10% to all other interactions equally. 

In Google Analytics, it’s also possible to create custom attribution models, though this is obviously for advanced users who have clear ideas of the way that site visitors commonly work their way through the sales funnel. 

Sentiment Analysis.

Sentiment analysis is the process of detecting positive or negative sentiment in text. It’s often used by businesses to detect sentiment on social data, gauge brand reputation and understand customers, 

It can be used when analysing customer feedback such as survey responses or social media conversations. You could use sentiment analysis to automatically analyse 5,000+ reviews about your product helping you to understand if customers are happy about your customer service. This is qualitative and quantitative data in one. 

Companies like Brand Watch use AI to conduct real-time sentiment analysis for large businesses. This yields insights that can help you position campaigns and messaging more effectively. 

Sentiment analysis might tell you that your pricing plans aren’t affordable for the lower end of your target market. You could then adjust your plans to include a lower pricing option and then create a marketing campaign that centres around those users. 

Conclusion.

Digital marketing campaign evaluation is tricky but there are many tools available to you to understand what’s working and what needs attention. Having a lot of different tools, doing different parts of the evaluation job can soon become unwieldy. 

With the advances in automation, machine learning and CRMs, it’s not only possible to track every interaction with your product but you can aggregate insights that will lead to more effective campaigns. Attribution reporting also makes it possible to assign marketing value at each stage of the journey.