Harness the Power of Marketing Campaign Orchestration

This presentation is from Timo Kohlberg and Doan Than. You will learn here how to harness the power of marketing campaign orchestration by:

• creating orchestrated experiences with great content
• driving hyper-personalisation across touchpoints
• leveraging real-time insights along the entire customer journey.

Hi, my name is Timo Kohlberg. I would like to get you thinking about your favourite coffee shop brand. Why do you go there? Is it about the product itself?

Well, of course, the product needs to be good. But it’s really more about other factors like the atmosphere in the coffee shop. How do I pay? How to order? For example, here in the USA at Starbucks, you can order your coffee and pay right away with an app. Then you can pick it up without waiting in line. Today, it’s more about the experience than the product.

We, at Adobe, identified 5 key pillars for customer experiences.

Content Velocity: Content creation is crucial in a world of so many devices and channels.

There is actually the role of Adobe campaign within Adobe Experience Cloud, being the orchestration engine sitting right in the middle.

Adobe Experience Platform lets you handle about everything from:

• advertising
• customer acquisition
• converting customers into turning them into context on your website with analytics cloud
• to personalise each and every experience you have with them within the magento commerce cloud.

Again, Adobe sits right in the middle as an orchestration and personalisation engine.

3 key pillars to achieve cross-channel orchestration success

1. Orchestrated Experiences

First of all, experiences need to be consistent and optimised for each device and each channel. It’s not enough to deliver stand-out email or mobile experiences, while have other experiences falling short on other touchpoints and channels.

2. Hyper-Personalisation

Think about customer data on steroids. Obviously, brands and accounts need to add transactional data to that. Think about the buyer behaviour on your website and then integrate other data sources like a propensity score for example.

3. Real-Time Insights and Journeys

More and more real-time insights, journeys, and information identify where customers are in their journeys, powered by the context you can deliver.

1. Orchestrated experiences start with great content

Marketers should not only think in the context of beautiful images, and channel optimisation, but also about the content process.

I like to call it the content supply chain. From creating beautiful content to managing that content, optimising, and delivering that content.

a) Content is the fuel of orchestrated experiences

• Take a look at sourcing and creating the best possible content. You should obviously have beautiful brand content from your agencies or internal designers. However, think also about integrating music-generated content into your communications.
• Streamlining the content management process with digital assets management. Use a content creation platform, where you can manage, optimise and deliver that content through solutions like Adobe Target and Adobe Campaign.
• Optimisation here is crucial. So, optimise delivery for all the important channels for you and your customers. Everything that relates to digital like website, mobile apps and any other interactions you have with your customers. If you are a retailer, you have a point-of-sale or a commerce/webshop you want to integrate. Basically, everything really should go towards one-to-one interactions through personalisation of content across channels like email, mobile, offline, and even the Internet of Things.

I’m going to show you a quick example of how our customers transformed the way they deliver their content.

b) A Content Transformation from single interactions

So, here is an example of Virgin Holidays, a well-known UK travel company.

So, above you see how they communicated with customers before choosing Adobe and Adobe Campaign.

This is a representation of a journey from someone booking travel. You can see how the situation was before (from a booking, and a payment reminder to an online checking). All this information from a data perspective was stored in different solutions, siloed, and not really available to all of the marketers.

From a visual perspective, there were also different systems delivering those messages and emails.

So, what I want to show you now, is the situation of the first campaign they ran.

C) To beautiful and consistent conversations

So, they had a content transformation to beautiful and consistent conversations with their customers by personalising content. Sometimes it’s as easy as including a booking code in all this information to reduce calls to the call center, for example. Besides, it is something that affects the bottom line.

2. Hyper-Personalisation is powered by data

Now, it’s time to talk about the usage of that data, its relevancy through hyper-personalisation, together with the content we just talked about.

a) Hyper-personalisation with the integrated customer profile

Obviously, think about the data you have in-house over the course of an individual customer journey.

You can actually build that single accessible view by combining information from channel preferences with online and offline channels. Then, bring that into a consistent campaign history. We will actually see that in the live demo, how it looks.

Here is an example from one of our retail customers.

b) Integrated Customer Profile – DNA for Campaign Management

We have two main data dimensions:

• Enterprise data: it is still the predominant data source for most of our customers (80 %).
• Digital Interactions encounter 20 % of data coming from those digital interactions and campaign data.

Above, you see different metrics you can track and combine in the integrated customer profile.

It’s really much more than just standard demographic data. Try to use all the customer data in-house as well as captured data based on what you actually do and what they prefer.

c) When Data meets Content

Again, in this section, I want to show you two examples of our customers.

• Travelocity, US travel brand, part of Expedia – Hyper-personalisation at scale.

In this case, it means they use all the information they have to create and send their newsletter.

For example, at the top, you see the mobile information they have on someone. If they know that a segment or a specific contact in their database hasn’t yet downloaded the app, they would push automatically that as the first content in the email.

Travelocity sends billions of emails to its customers. So, it’s very clear they couldn’t handle that manually anymore. They need a solution like Adobe Campaign, which can automate that personalisation process.

d) User Preferences and Customer Feedback

Secondly, in terms of data acquisition, the third dimension underestimated by many brands is ‘preferences’ from your customers.

So, in this instance, Travelocity has what they call a ‘travel profile’. In the preferences’ section, customers can choose what kind of deals they want to receive.

Based on this information, all the personalisation done through email and website is tailored to the needs and preferences of their customers.

3. Real-Time Insights and Journeys are driven by Content and Artificial Intelligence (AI)

For the last section, it’s crucial to integrate real-time information (behaviour). Marketers must know as well the context of where the customers actually are in terms of their buying journey phase. More and more of that is powered by Artificial Intelligence (AI).

So, again, 3 other examples to provide you with.

a) Connecting email to web

What you see above is a contextualised content and offers based on the search history of someone on the website.

So, someone just searched for holidays in the Bahamas. On the next day, they would receive a tailored deal based on their search history and how they interacted on the website. If they don’t want to book right away, they had the option to save it to their deal allows them to get more information about the destination and offers in the future.

On average, they have a much higher open rate and click-through rate.

b) Content needs to BE contextual and orchestrated

The second example from one of our travel brands in Europe is Heathrow airport.

On the left-hand side, you see how they use and contextualise all the information from the integrated profile.

I am just highlighting 3 things here:

• Product based on previous transactions:

You see at the top, it’s actually offers pushed based on previous transactions. In this case, someone has already parked at Heathrow airport; Consequently, they can actually push an offer for parking for the next flight.

• Exclude known users:

It’s important to incorporate mobile information not just in a mobile message, but also in other channels like email. So, exclude known users from offers, like downloading the app.

• Tailored brands/offers to segment:

If you are at the airport, they want to drive you to specific shops and brands. They are the right ones for the specific segment.

Think about going into the terminal area for the security check at the airport. If you have downloaded the app ‘Heathrow airport’, you may receive personalised push notifications for discounts or loyalty points in restaurants.

It’s working really well and they can tailor those messages and offers based on where you are in a specific terminal. But they also use more and more beacon technology to send you messages when you walk by a restaurant. This is a great example of orchestrated experiences with digital as well as also at the physical location (airport).

c) Email experiences powered by AI/ML

As a last example for this section, I want to show you an example of Adobe Sensei, our AI machine learning framework.

We have a feature here called ‘predictive subject line optimisation’, where you can test your subject line before you send out your newsletter.

So, think about the case you have to send out a newsletter on Thursday and do not have time to do an A/B test for your subject line. With this feature, you will be able to test your subject line based on the previous sent-out. It will actually predict open rates for that subject line. It will give you the feeling of whether it’s too long or too short and also find some optimisation with different categories.

d) An orchestrated Omni-Channel Experience

To sum up, the integrated customer profile consists of enterprise data, but also more and more digital interactions.

Then, bring that together with Content through the Content Supply Chain, to manage and deliver across different optimised channels.

Through this representation of a customer journey across many channels, we can learn more about the customer based on the data. So, you might start with the channel that activates customers to download the app, by sending a push notification.

In some instances, you might want to:

• send a direct mail or a catalogue
• integrate the call center into the website
• send a re-marketing email like we’ve seen with Velocity.

This strategy is focused on all relevant and meaningful experiences.

Perfect, so, I want to hand it over to Doan to take a live look at a demo of Adobe Campaign.

4. Adobe Campaign Live

Let’s start the demonstration by having a look at the data powering the Adobe Campaign Platform that is giving you an internal 360° view of the customer.

Here, we can view a profile I kept within the Adobe Campaign.

Adobe Campaign has an internally customisable relational database, which can be extended and modified for your specific business needs. We’ll have a look at what a profile looks like in Adobe Campaigns.

Above it is Kevin Blake and we can store all marketing data related to Kevin such as:

• name
• location
• aggregate scoring inside the platform, which can be used to trigger and power message sets from Adobe Campaign.

Please note that no two databases inside Adobe Campaign are the same. They are tailored and customised towards your business requirements.

On the top, we have all relevant business tabs related to Kevin as well as tracking logs.

These tracking logs:

• keep track of all messages you send out
• show you how customers interact with them.

On ‘orders’ tab, you can keep track of orders that came in:

Data can be used to trigger personal communications as required by your business.

This is not only linked to orders, this could be ‘mortgages’. Just depends on what your business needs are in terms of campaign management.

If we move to the workflow end, we’ll have a look at Adobe Campaign powerful and customisable workflow engine.

So, here on your right (see the below screenshot), we have a canvas, where you can drag and drop different parts of your customer journey.

This customer journey can be digitalised on this canvas. You can see where your customers are in each step of the customer journey that they are on with your brand.

On the left (see the below screenshot), we have ‘Union’, which we can drag and drop on the canvas to query for and deliver many channel messages to your contacts.

One particular note, we have many channels, which you can set up with Adobe Campaign, it’s not just emailed.

You can set up (as shown below):

• push notifications
• direct mail
• in-app messages
• SMS.

This will allow your users to create a schedule in multiple different ways. You can send it through multiple mediums. It will be based on your customer journey phase, their experiences, and preferences.

You can also do some basic data management notes (see below), where you can:

• enrich customer journey
• update data or save data into different tables or platforms.

All these below notes combined to create a rich contextual customer experience for your contacts, as they go on your brand journey.

Let’s have a look at how we can create a relevant and personalised email within Adobe Campaign.

So, inside the Adobe Campaign, there is an in-built drag-and-drop HTML render. This allows you to easily and seamlessly create professional and customisable emails, that can be delivered under the build I showed you earlier.

The fragments can be dragged on the email canvas, adaptable without a single amount of code.

Adobe Campaign comes from Adobe Sensei, which is an AI machine-learning engine. It enables to use of Adobe Sensei to make better sense of the data and create predictive sales analytics.

So, here we have a subject line optimisation:

We can see below how customers in the past have interacted with email. We also receive different suggestions on how to make this subject line better. Adobe Campaign Sensei will give you a better view of how these emails might perform in terms of ‘opened’.

So, Adobe Campaign is not just about creating a workflow and laying a run-out. It runs a report and continues to be innovative in these features.

With Adobe Campaign, it’s easy, flexible, and customisable with data points collected in real time. The preview report will show you the value of quickly getting a sense of different views. This allows you to get a better understanding of your marketing performance. Furthermore, it gives you a better idea of how attractive you are as a business.

Metrics such as ‘dimensions’ can be dragged and dropped to points. Points are accessible, interactive and all interconnected to devices.

Visualisation is simple, responsive, and re-sizeable.

With Adobe Campaign, you can set dates and apply different metrics depending on these dates.

These reports will automatically update to see what you are doing and tracking the past 6 days. On the left (below screenshot), you can drag different devices and see how your email campaign is doing in this regard.

Finally, we want to make sure that our customers actually make the most of their investments with the Adobe Experience Cloud, called ‘Experience League’.

At last, we also recommend you these two free whitepapers downloadable from our site:

• Mobile for the win
• Get out of your email marketing rut.

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How to understand your website traffic data with Google Tag Manager

Google Tag Manager

I signed up for a Learn Inbound Marketing event a few months ago on Google Tag Manager data insights!

The presentation delivered by Tom Bennett is divided into 5 topics:

1. Understand and invest in your data
2. The challenges of engagement traffic
3. Google Tag Manager can help us improve our data collection
4. Smarter segmentation
5. Work with your developers.

Since it is quite technical, I recommend you to sign up for Google Tag Manager and follow the process he is talking us through.

If you have a more audio or visual memory, you will find the podcast transcript and powerpoint presentation further in this article.

PODCAST TRANSCRIPT

1. Understand and invest in your data

Google Tag Manager helps you measure success in Google Analytics.

If you take away only one thing from this evening, it’s understanding and investing in your data.

Google Analytics is designed to work well. Out of the box implementation with zero customisation, it’s very easy to set up.

But let’s be honest, ‘the one size fits all’ approach to marketing is rarely the best. Indeed, the needs of your business and the Key Performance Indicators (KPIs)  of your website are unique.

Consequently, data collection is crucial for the entirety of the analysis process. It doesn’t matter:

• how many segments you build
• or how  many goals you define,

if you mess up your data collection, it will screw up every other stage, too. So, what the value of the insights your analytics software will give you is directly tied back to the investment you have made in data collection at first stage of the whole process.

So, today I’m going to run through few examples of how a smart implementation of Google Tag Manager (GTM) can dramatically improve the relevance and quality of the available data in Google Analytics.

There are no magic bullets, but I hope everyone here will be able to take away at least one technique they weren’t previously aware of and get some of the value from it.

2. The challenges of engagement traffic 

So, we are going to start with engagement tactics, specifically content engagement, because so many organisations are stuck trying to answer meaningless questions like ‘why is that Bounce Rate so high?’

The problem with that is that you see reports saying things like ‘Our content is really good because our sitewide’s average bounce rate is down to 10%’. But this statement is worse than misleading and is often inaccurate.

in fact, many people who use Bounce Rate as the primary KPI don’t actually understand what Bounce Rate is measuring. The effect of this is that the individuals are encouraged to fix the metric rather than the underlying problems, which are of course unique to your site.

So, let’s refresh ourselves with the definition of a Bounce Rate.

Google finds a single page session calculated as only being a single request through the analytics server. What that typically means is that a user arrives and leaves your site via a single page without doing anything on any other pages in-between.

It’s important to remember that sessions are really these fictional constructs Analytics come up with when it processes your data.

Analytics doesn’t know how long a user spends looking at a particular page. It doesn’t set any kind of timer to measure when a session started and when it ended. All it has is this raw hit data:

• pageviews
• events
• transactions.

From this data, it extrapolates and builds this arbitrary notion of a session, which starts and ends after 30 minutes of inactivity (a time gap between hits, midnight or a campaign change).

Now, incidentally, this is why if you commit the sin of tagging your internal links with UTM parameters, you generally see a very high Bounce Rate on most pages. Navigation via those links will result in a new session starting.

So, in order to calculate, divide as the ‘average time on page’, it actually measures how long it takes until the next page is received. To get the session duration, it just measures the time between the first and the last ‘hit‘ in that session.

So, when it uses ‘Bounces’, GA doesn’t have enough data to generate all those metrics it reports such as average time on page, for example.

Indeed, there is no second hit it can measure against to calculate ‘time on page’, which is why it’s not a really good metric to use as your sole KPI, especially when used in aggregate. It becomes meaningless because the questions we can’t answer are substantial.

We don’t know what the user did on the page, how valuable they are to us as potential customers. We don’t even know either if:

• the website functions properly on that device
• they read every single word of that content and
• they bookmarked it to come back later.

Ultimately we lack data.

3. Google Tag Manager can help us improve our data collection

A smart implementation of Google Tag Manager (GTA) is necessary.

• CONTROLLING AND TWEAKING THE BOUNCE RATE

So, we will stick to the ‘Bounce Rate’ for a while because it demonstrates some good points. You do have control over the bounce rate calculation.

Indeed, you can control which hits will affect Bounce Rate(BR) and which don’t. To illustrate this point, this is an example of a client I recently on-boarded. They received a 0% BR on most of their pages and couldn’t figure out why.

Ultimately, what happened is the development team, which configured not just the standard page but also an ‘Event‘ that fired when all the dependent resources on the page were ready (images, skyscrapers…).

Consequently, it was impossible to have a single hit session because every page viewed was firing two hits. That’s the same principle why really bad WordPress implementations will often see low Bounce Rate because you get duplicate tracking code, i.e two hits per page.

But don’t worry, you can control which ‘events’ effect the Bounce Rate by using the ‘Non-Interaction Hit‘ Flag. You can set this very easily in GTM when you are configuring your ‘event’ tag to  ‘Non-Interaction Hit’ to ‘True’. The BR for the page, on which this ‘event’ fires will be calculated as if the event wasn’t there.

So, for example, if you absolutely have to fire an event when an auto-playing video starts, just set ‘Non-Interaction Hit’ to ‘True’ and the BR will be calculated as if our second hit wasn’t there and would be more accurate.

This idea of using ‘events’ to control our BR plays nicely into the whole idea of ‘On-page Engagement Tracking‘, in a single page new session for eg.

A lot of people started using some of GTM built-in triggers to try and manipulate the BR. For example, GTM has a ‘Timer‘ trigger and by using that, you can avoid relying on GTM arbitrary ‘time-on-page’ calculations.

But one trigger I’m really fond of is the new ‘Element Visibility‘ trigger. To illustrate my point, I picked random examples from the Learn Inbound website. Let’s say you have strategically distributed throughout your longer pieces of content ‘Calls-to-Action‘ like this email sign-up widget.

You may be interested in who is getting to that position in your content or preventing people who got that far through your guides from being counted as Bounces.

If you strategically position these kinds of elements at different positions throughout your various page types, then the ‘element visibility’ trigger can be a powerful way to take advantage of this.

So, we’ll set up a trigger now. As you can see, it lets us define an ‘event’ based on either an ID or a CSS selector. We have control over when this trigger will fire. We can set it to fire when the element is on-screen for a certain duration as your user scrolls through your content. Or it has to be visible for a certain percentage of the element in the ‘View post’. You can even control how many times it will fire if the element appears multiple times per page.

So, in this example, we use this trigger and other triggers to fire an ‘event’ when someone starts scrolling through our content. Obviously, that would be a ‘Non-Interaction Hit’ trigger, when they view the ‘call-to-action’ and then when they reach the footer.

So, by drilling down to a particular page and then viewing this kind of ‘event’ data, it can be very powerful in allowing us to get a sense of who is actually reading our content versus just bouncing immediately.

It can also be segmented by audience types and page to give us insight. This way, we can actually stir our internal linking or content strategy, based on what we learnt about which pages people are engaging with. It can be specific to your other page types. So, needless to say, it goes much further than tweaking the Bounce Rate.

• TAILORING YOUR DATA COLLECTION METHOD AROUND THE PAGE TYPES

Your data collection method needs to be tailored not just to your business but to that different page types, the different page types of content on your site.

As an example, we are going to look at ‘Interactive Content‘. It’s an interactive piece of content marketing which lets you calculate the heating costs for their home. You can select your ‘Room Types’, ‘Sizes’ and ‘Glazing’. Then it will give you an approximate cost for heating.

Now, in a classic example of ineffective communication between marketing and developing teams, this was pushed out of the door with very little consideration given to its tracking requirements.

It is a shame because GTM is really good at letting us track high relevant interactions that would be taking place on a piece of content like this. Interactions which are very relevant to the kind of audience we are trying to appeal to with this content.

One of the best ways that allow us to do that is with the ‘Custom Event‘ trigger type. In practice, you will ask your developers to implement a piece of Javascript code into your Application. This will push an ‘Event’ to the ‘Data Layer’. All it does is provide us with something that we can listen for at the other end in GTM.

In this instance, we have touched the ‘Data Layer’.push’ in the ‘Event’  and we have pulled ‘CalculatorGo’.  To listen for this as a trigger in GTM, all we do is set up a ‘Custom Event’ trigger. Then, name the ‘Event’ that will appear in ‘Data Layer’ ‘CalculatorGo’.  We can use this to fire a Google Analytics Event Tag, so we know how many people are using interactive.

• USING CUSTOM VARIABLES TO GET MORE GRANULAR

We want to know how people are using this content. The purpose of it is to appeal a wide audience and drive more revenue. Ultimately we want to know how people are engaging with this content we built.

So, let’s say, for example, we want to know which option uses our selecting when they use our calculator. We can supplement our ‘Data Layer’ Event with two data variables. We’ve gone from ‘Room Type’ to ‘Glazing Type’. These simply populate the ‘Data Layer’ with variables reflecting the user choices at the moment. At the moment, they hit ‘Go’.

Then, we set these as data layer variables in GTM. This means they are now available for us to use in our tags, in our Google Analytics ‘Event’ Tag, for eg.

So, here we have referenced down variables as the ‘Event’ action label respectively. This will give us relevant data about:

• our audience
• what they are using our interactive content for
• and what they are looking for.

We can use this to iterate not just the layout, the functionality of the page, but also use it as the basis for guiding our content strategy or improving our lead nurturing process.

You can extend this approach a long way by using our ‘Goals’. By segmenting to a particular campaign for eg., we can then see how people are engaging with this content and analyse that in isolation.

Thanks to native ‘variable types’, we can get quite creative.

So, to keep the same example, we could set up an ‘Event’ value which fires when someone engages with our piece of content and we can set the value based on what we know about them as users.

We could come up with systems using ‘Lookup Tables’  or even ‘Custom Job Description’ running in GTM, which will assign an arbitrary value to them based on how valuable they are to us as ‘leads’. Then set this as the ‘Goal’ value in GA.

This will give us a sense of how valuable that traffic is as potential customers. So, we can see the absolute number of conversion, but also an approximation of the fair value to us as customers.

And of course, when segmented based on a particular campaign, we can start to gauge the content value of our marketing content efforts.

4. SMARTer SEGMENTATION

The last area I want to explore is using GTM to better group our content.

• CONTENT GROUPING

For example, if we wish to segment our content strategy into different groups based on the offer, we can do that with the ‘Content Grouping’. It’s very easy to implement.

We can create the ‘Content Grouping’ at a ‘View’ Level. Then, we enable a content tracking code based implementation, and give it an ‘Index Number’ of ‘1’. Afterwards, we can set up the actual author using a ‘Data Layer’Variable’.

By using the ‘Data Layer’, you can work much more smartly. We get our development team to implement the ‘Blog Author‘ as a ‘Data Layer Variable’.

Same principle as we did earlier for our interactive content and then we can reference that in our ‘Pageview’ Tag.  Under ‘More Settings’, we can reference the ‘Data Layer Variable’ in there, so that every page you hit will fetch the account of the author from the ‘Data Layer’. Then it will fire that as the value for that ‘Content Grouping’.

As a result of this, you can view an aggregate performance of pages by particular authors and get a sense of how they perform as a whole. That’s very useful data when it comes to assessing how well your content strategy is performing.

• CUSTOM DIMENSIONS

To segment further users, let’s look at particular groups of our audience like ‘Behaviours‘.

For example, we might decide to track users who comment on our blog. Then, view that ‘Audience’ group as a separate segment of traffic with ‘Custom Dimensions‘.

Whereas ‘Content Grouping’ allows us to organise our pages into logical groups, ‘Custom Dimensions’ let us record extra like non-standing data on top of GA standard dimensions. They are very flexible in how they let us do this as well.

Remember that every hit which goes to GA has a different scope. For eg, the ‘Pageview Hit’ has a scope limited to that page view. But ‘Landing Page‘ has a scope which applies to the whole session.

 Now, it’s the ‘User Level Scope‘ we are interested in because it lets us apply the data from that hit from the user and all of their subsequent interactions on that website.

So we set it up at the ‘Property Level’, giving 20 ‘Dimensions’ per ‘Property’. We’ll give an ‘Index number’ of ‘1’ and set the ‘Scope’ as ‘User’. So, back in GTM, we are going to fire these ‘Custom Dimensions’ as part of an ‘Event’ hit that will be launched when someone is coming on our blog.

Then under ‘More Settings’, we can set the ‘Custom Dimensions’. We will put an ‘Index number’ of ‘1’ and a ‘Dimension Value’ of ‘Commenter.

In terms of trigger, we can once again use a ‘Data Layer Event’. To run through what happened in the back of this, I user a ‘User Submitted Content’. That action will push an ‘Event’ to the ‘Data Layer’, which we are listening for in GTM.  GTM fires out a normal GA Tag ‘Event’. That hit goes on and includes a ‘Custom Dimension’, which defines the user as a commenter and that will apply to all his subsequent actions on the site as well.

As a result, we can now view the behaviour of our engaged users as a segment in GA. We can also see how they differ from our wider readership. We can use that as the primary dimension in a report to analyse the results in our funnel.

5. Work with your developers

It is important to collaborate with your development team when it comes to data collection.

It is really vital that you understand how these technologies work so that you can communicate effectively with your development team.

Google Tag Manager is kind of unique in it’s an inextricable tool for both marketers and developers. They are about tracking what users do, how valuable they are for us as customers. But Google Tag Manager is also a complex Javascript Application. You need to have a familiarity with Javascript in order to work properly with it.

The ‘Data Layer’, which kind of underpins a lot of the techniques that run today, is in international waters. If you look at the kind of data encoded into the ‘Data Layer’, its semantic information about:

• our audience and our customers,
• what they are doing

enforces a shared language.

A well defined and maintained ‘Data Layer’ means the data about your content and interaction that take place are accessible in a format independent of any platforms or technology. You are not reliant on scraping your HTML. You can instead make the data points you are interested in available to use.

However, you need to get your development team to implement it. Indeed, it is a very powerful tool that can easily break your website. The ‘Data Layer‘ should be regarded as a pre-requisite for good measurement.

I will give you a gift for your developers. It is the ‘Javascript Error‘ trigger tag. All it does is fire an ‘Event’ tag when the browser encounters an unquoted Javascript error.  This is normally the information only available in Javascript Console on your developers’ machine. It lets you fire an ‘Event’ whenever a user’s browser encounters an error in GA.

Thanks to the built-in variables of error messages, error URL, error line, information which the user wouldn’t be seeing, we can the fire the information to GA on real-world usability issues. Don’t forget to set that ‘Non-Interaction Hit’ to ‘True’. This will take no more than 5 minutes to implement. It will get real-world testing of your data about:

• what’s breaking on your website
• where
• and for who.

You can cross-reference it with the other built-in dimensions as well, like upgrading system and browser. You can give that information to your developers, segment it by page. And you will make your website more accessible, functional. The value of the insight you can get from your analytics software is tied to the investment you make in data collection.

By demonstrating success and by unlocking the kind of actionable insights that you need, you can justify whatever it is that you are looking for:

• bigger budgets
• more innovative projects
• more development time for your team
• and ultimately whatever you need to do your job better.

For those who would like to download the Powerpoint slides containing more visuals and his contact details, click on the link below:

Google Tag Manager Insights Powerpoint presentation