The key word here is ‘event’. An event is a record of a single instance of behaviour taking place on a website or app. It’s tied to a user’s identity and useful information (attributes) can be stored inside it.

This practice is sometimes referred to as trigger marketing, event tracking, event driven marketing or event streaming. The sheer power and potential of this new type of marketing is driving massive advances in the way digital marketers, growth hackers and product marketers work.

There are two components: managing identity and recording behaviour.

Identity

When a user visits a website or mobile app they are automatically assigned an anonymous identity. The anonymous identity is used to store the record of their behaviour until, and if, the user becomes ‘identified’. Identified users are known users who already have a record in the user database. At this point, the anonymous identity and the known identity are joined together so that all past behaviour recorded against the anonymous user is now stored directly against the known user.

Without a user’s identity we would not be able to assign the stored behaviour to a particular person. This would limit our ability to communicate with the user (we can’t send them an email or push notification if we don’t know who they are). Instead, we would receive general data about the way the whole service is being used by all users (think Google Analytics). Identity based marketing also allows us to track users across different devices more easily.

Basic Recipe of an Identify Call

analytics.identify([userId], [traits], [options], [callback]);

Behaviour

Behaviour is information that describes how the user interacts with the website or app. It is recorded as an ‘event’. An event is a single instance of measured behaviour; a single event in the journey of the customer. The event could describe a users explicit action such as ‘Clicked on Playlist’ or an implicit action such as ‘Moused Over Playlist’.

Basic Recipe of an Event

analytics.track(event, [properties], [options], [callback]);

Attributes can be parsed in to the event allowing for unique, and highly relevant knowledge to be stored inside the event itself. For example, the playlist name, the playlist ID, the duration, and the description could all be stored in the event ‘Clicked on Playlist’.

analytics.track("Clicked on Playlist", {
playlistName: "Australian Top 50",
durationMins: 132,
playlistID: 2388383820022992,
playlistDescription: "The latest and greatest hits topping the charts down under."
});

By measuring behaviour in this way and storing key information about the behaviour inside the event, we can send the user a much more contextual message or prompt when trying to engage them.

Origins

Event stream processing has long been used by software engineers to build event-driven systems. An event would be use to record a significant change in the state of the object. By measuring behaviour in such incremental detail we are able to more clearly identify exactly where the user stops in a given flow or process. Algorithmic trading desks are an example of such systems. In this example each change in the price of a stock is measured as a single change in state, down to the cent. By monitoring all movement in the stock price, an algorithm can treat each event as a new state, and better predict the next movement based on the current and past states. Such granular measurement allows the algorithm to react quickly and accurately. Contrast this to simply knowing the starting price and the current price of a stock at any given time of the day (the way humans typically monitor stocks).

Event-based marketing is literally the marketers equivalent of this practice. By recording much more information about a user’s behaviour—each change in the user’s state—we know exactly where a user is in their journey and can construct a highly relevant and personalised message to deliver to them.

The word ‘event’ might ring some bells for us old-school marketers. Google Analytics has long offered the functionality of recording and storing custom events about how users interact with the product. This was great, and certainly offered us some insights into those more granular and unique behaviours, but there was always one problem… identity. Who are these people?

Example

Let’s use a typical abandoned cart campaign as a way to compare event-based marketing to traditional behavioural campaigns.

Traditional Behavioural Campaigns

Typically when implementing an abandoned cart campaigns we track two stages:
1) when the user starts the checkout process and
2) when the user successfully checks out.

More advanced implementations might track the step in the checkout process the user was at. This allows them to send the user back to the exact step they were up to. In total, most abandoned cart campaigns are measuring two or three stages. More often than not, this is done by querying the clickstream data (specifically the URL path) for users who have viewed the ‘checkout page’, but not viewed the ‘payment confirmation’ page. Because of the vagueness around this method of tracking, we typically wait 2-3 hours before sending the abandoned cart campaign.

Event-based Campaigns

When implementing an event-based abandoned cart campaign, we can record many more events:
1) User adds item to cart
2) User starts checkout process
3) User confirms shipping details
4) User confirms billing details
5) Payment successful
6) Payment unsuccessful
7) User successfully checks out

Each time a user triggers the next event in the sequence their state changes. This helps clearly indicate the exact point in the flow that they are up to. The moment events stop being received (the user abandons the checkout process) we need only wait a short period of time before sending the abandoned cart email (20 minutes for example). If the user stops at step 4, where they have confirmed their billing details but no result has been received for payment, we need simply send them an email encouraging them to finish paying.

On top of this, we are able to store information about the progression through the cart inside the event itself. This can be parsed through from the email to the target (website or app) by attaching the information in parameters on the link.

How to Implement Event-based Marketing

Event-based marketing significantly improves the capability, speed and quality of marketing. The technology is rapidly advancing and new tools are emerging designed specifically around these capabilities. This comprehensive guide to event-based marketing is designed to help digital marketers utilise javascript “events” to trigger marketing, product, analytics, advertising and communication campaigns based on user behaviour.

To be clear, this is not a guide about promoting physical events. This is a guide about using javascript based events to automatically trigger marketing.

In the context of digital marketing, “events” record a single instance of a behaviour occurring on your website or app. They are called events because:

1. they record a change in state, and
2. Javascript technology uses events to trigger functions.

I’ve worked with event-based marketing since 2013 and in this article, I’m going to teach you everything I know about this field of marketing.

Does event-based marketing work?

Yes, event-based marketing works and it’s probably the single biggest opportunity for growth in almost every business today.

I’ve been using event-based marketing for around six years now. I’ve implemented it successfully in my own business, and have helped many other companies implement it. In every single case, those businesses saw an immediate company-wide increase in every metric that matters. From revenue to email deliverability. I’ve literally seen 400% to 600% increases in conversion metrics overnight. Event-based marketing absolutely works.

The performance of every single marketing channel and activity is enhanced when event-based marketing is added. Even interstitial popups convert well when enhanced with event-based marketing.

Yet, despite all of this… very few people know how to do it.

This makes sense though because it’s virtually impossible to learn. There is literally zero content online about it. Not a single guide or course… a few articles here and there, but that’s about it. So, being the content-savvy marketer I like to think I am, I started writing about it (and teaching it in real life). This was a great decision because it’s helped me refine all of the content I’m about to share with you. The diagrams, the explanations, the metaphors, the strategies and most importantly the application of the concepts are all better because of the real-life testing that has taken place in the classroom. Let’s begin…

Technical background to event-based marketing

It wasn’t until the early 90s that marketers first started tracking people visiting their websites. Unlike the way most marketing professionals approached their job at the time (think Don Draper), this new breed of marketer was fascinated by measuring whether their marketing activities actually worked. These data-driven-pioneers were the first ‘digital marketers’ because of one thing: data.

Access to data was the turning point because it closed the feedback loop of marketing. Immediately every single marketing function became measurable, which in turn creates an opportunity to optimise our marketing. Data also speeds the entire marketing process up; if you’ve ever tried to optimise a website with no traffic you’ll know what I’m talking about.

From this moment on, data gave us the ability to measure our performance as marketers and compared to the incumbent alternative of little to no measurement, it probably felt like it was all happening in real time. Indeed, this was the birth of digital marketing, and the data source we came to rely on was server logs.

Server logs

Initially, the ability to actually measure the traffic to your website and the pages people were interested in relied on the most basic analytics technology we have: server logs. Server logs still work to this day. They show us the documents being requested by people who visit our website. When PHP, XML and HTML were the default web languages this worked well because every change in the state of a page (and the information contained upon it) relied on a call being made to a server. The typical user path on a website would look something like this:

The server log would tell us which documents were being requested on the server, and in which order. Beyond this, marketers couldn’t do much more… but neither could websites, so the data still felt pretty powerful. However, far more meaningful metrics would become available if we moved the tracking scripts to the client side. Enter ‘click-stream analytics’.

Click-stream analytics

Although they were not the first with this technology, the release of Google Analytics in 2005 democratised online analytics by introducing a free analytics package that would enable anyone with a website to begin collecting in-depth analytics about site usage.

The technical innovation was based on the repositioning of the data collection away from a server-side implementation to a client-side implementation. Rather than tracking document requests on the server, we would monitor requests from the front end of the website itself using a piece of javascript. In other words, we tracked the “click” side of a document request, rather than the response side of a document request. Clicks are an important evolution because they also represent a shift towards intention based metrics.

This repositioning of tracking allowed us to obtain an ever increasing number of new data points. Things like bounce rate, time on page, session durations along with new browser information such as screen size suddenly all became possible. The click-stream still recorded the movement of a user between documents, but it leveraged the user’s browser to achieve it (rather than the server).

This was a major breakthrough but it was appropriate given the changing purposes of websites. Rather than websites being brochures online, websites were becoming shops… and applications (such as forums and trading sites like eBay). This change in the way we used the Internet also spawned the development of a new series of technologies designed to facilitate a more lightweight transfer of data between a user (client) and the server. Not only would this speed browsing experiences up, but it would also take an enormous computational burden off the servers themselves (simply by reducing the size of the requests).

The things we cared about, such as a reply to our message or the change of an item’s price on eBay represented a very small portion of the overall HTML document. So instead of needing to reload the entire document, we were increasingly only reloading the portions of the document that had changed (often just a single line or value). AJAX and Javascript languages offered a way for websites to achieve this, by transferring small packets of data within the page itself.

Google Analytics quickly added support for these in-page changes of state using a new report called “events”, but the fact that user data is not allowed inside Google Analytics largely renders this function useless. Events in GA can be used for goal tracking and simple reporting, but not much more. This was not a problem for click-stream analytics at first, until Javascript took over most of the web in the form of Single Page Applications (SPAs). Yep, I’m talking about Angular and React, along with back-end frameworks like node.js.

Suddenly a single document became an entire website.

Event-streaming analytics

As websites quickly evolved into web applications a document based tracking method was no longer adequate. Users could spend 10 minutes on a single page clicking, liking, saving, posting and otherwise interacting with the page despite the document path not changing. Think of Facebook.com’s home page news feed for example, as a user scrolls through their uniquely personalised news feed liking and commenting on posts, they are creating an enormous amount of data, but the document path is not changing. In this scenario, a click-stream based analytics tool like Google Analytics would simply report time on page of say 10 minutes with a 0% bounce rate.

The fact that all of these sites run on Javascript technology means that all of these interactions are already being recorded using javascript events. Amongst other things, these js events are used by the application to change what the user sees (the DOM) and how they interact with content whilst avoiding reloading the entire site itself. These events trigger client side or server side functions and can transfer data… again, all without requiring the page to be reloaded.

For example, imagine a user finding a product on an e-commerce website, adding the item to their cart, and commencing the checkout process. The event-stream would look something like this. Notice how it’s sitting on top of the document (server logs) and click-stream.

You can see from the diagram above that the click-stream is really not that useful at all. So, now we arrive at the present day.

Event-based marketing today

Today, javascript events are running most of the front-end and back-end of websites and applications, but marketers… and product people… and even engineers sometimes just aren’t using them. Or are they?

In 2017 Facebook announced the transition away from the 8 default ‘conversion pixels’ to a new ‘smart pixel’. You’ve probably guessed it, but the old conversion pixel was a server log based analytics method, much like the 1px by 1px image contained within emails to record email opens. The old Facebook pixel would trigger a request to a document on Facebooks server, located at a unique path where it could then be mapped as a conversion. The conversion count was simply the number of times the document had been requested on the server. The ‘smart pixel’, again you’ve probably already guessed it, is a new javascript based event tracking script. Javascript events would fire, sending a record of an event having occurred back to the Facebook conversion server. The number of conversions would be equal to the number of times the event had fired. This matters because marketers are interested in who triggered the event, not just the fact that an event was triggered.

So, that leads us to the present day. Any marketer using Facebook advertising is already using ‘events’ to measure conversion (they just don’t know it) and the worlds number one analytics platform doesn’t support personalised event tracking. Can you see the opportunity?

What is an “event” in the context of event-based marketing?

Definition

An event is a record of a single instance of behaviour taking place on a website or app. It’s pinned to a single identity (known or unknown) and we can store useful information inside it.

Think of an event like a box that you can store useful information inside of. It gets automatically created when a user performs an action or a task (a behaviour) you are interested in observing and measuring. This box can then be stored, and sent anywhere you desire. If you want your email marketing platform to know about the event, send the event there. If you want to serve the user an advert in Facebook based on this behaviour, send the event there. If you want to create a report of the number of times this event was fired, you might send a copy into Amplitude to help generate the report. If you want to send a push notification a week after the user triggers the event, send it to Vero.

Anatomy of an event

There are three parts to every event:

1. An identity (even if it’s anonymous)
2. A unique event name
3. Attributes stored inside the event.

Again, an event is a single instance of behaviour with information stored inside it. People trigger events, which means we can attach an identity to the event. As marketers, this means we know what happened, when it happened and who did it.

Why do we use the phrase ‘event stream’?

As users move around our website or app, clicking and interacting with things, they create a stream of data. This stream describes the user’s actions in chronological order. The stream really matters because it helps us perform what I can only describe as ‘reactive marketing’. We can react to users actions in real time by creating conditional rules. For example: if a user triggers, “add an item to cart” and does not trigger “started checkout” you may wish to commence display advertising containing the products the user just added to their cart. The fact that events happen in a particular order means we can more easily build conditional sequences around our user’s behaviour.

Stateful and stateless data

Lastly, it’s beneficial to know about the differences between stateful and stateless data. This is a very technical concept, but it fundamentally underpins event-based marketing.

Stateful data allow us to create, store and read the memory of the data generated in the lead up to a stateless change in our database (like filling in a form).

Stateless data holds no memory of the past, it merely contains the most recent version of a record (such as the information submitted by the form).

Most marketing platforms were built for stateless data streams. This means that marketers can only react to stateless changes in the database, such as a user creating an account, adding an item to their cart or making a purchase. However, to build a truly customised event-based marketing program, we must be able to trigger marketing automation on the smallest changes, and these can be easily measured using stateful data points.

Right person, right message, right time

The post What is Event-based Marketing? appeared first on Will Egan.

Software as a Service (SaaS) – AARRR (colloquially called ‘Pirate Metrics’)

This should be familiar for people who live in the startup world. It’s the go-to framework when thinking about consumer behaviour and decision-making. A startup or a business that operates from a SaaS model can only be successful when each of the five AARRR stages are broken down, defined, measured, analysed and then optimised.

Acquisition

Acquisition refers to how your customers find you. There are many potentials channels out there (over 800 at last count), and I highly recommend reading this great article that covers the variety of channels by Gabriel Weinberg (the author of the book Traction).

Weinberg manages to shoot off 19 different channels. Some such as SEO, SEM and display ads might sound familiar, but have you considered community building? Or unconventional PR? There is more than one way fill up the top of your funnel up.

Peter Thiel, legendary Silicon Valley entrepreneur and investor says “It’s very likely that one channel is optimal, most businesses get zero distribution channels to work. Poor distribution – not product – is the number one cause of failure.”

The Bullseye Framework by Gabriel Weiner is another great framework to help you identify what channels are worth testing, in order to find that one scalable channel.

His article is structured whereby the 19 possible channels lie on the outside circle of a darts board, whilst the channels you should be testing lie in the inside circle on the board. The one channel that performs exceptionally well will be the metaphorical bullseye. Have a read.

These channels aren’t only relevant for acquisition however, or getting new users. For example, email marketing is great for top-of-the-funnel activities, but it is also one of the best weapons for retention, or referral. Have you had an email from a business that says, “we haven’t seen you around on our platform lately, we miss you!” These types of drip campaigns can be used across the entire user journey.

When testing acquisition channels, it’s incorrect to think about the funnel in the context of acquisition alone. As a great marketer, your mission is to consider the entire funnel. For example, whilst you might be getting someone onto your website for $0.30 with a display ad vs. $1.10 with Google Adwords the long-term value of these two users may be very different.

At first glance the display ad is a clear winner. But what if Adwords customers are converting 300% more often? Still a slightly worse option. But what if they are retained/repeat users at much higher levels, and even bring in more referrals? This is what you need to be thinking about in context of acquisition, not just the acquisition metrics.

Put simply, acquisition is a set of strategies and channels designed to acquire users. Acquisition is usually the last thing to be built-into most marketing machines. Often, there’s a minimum viable number of daily sign-ups (say 10 or 20) that most product-teams need whilst building the product and building the growth machine.

Activation

The next step is activation. It’s our view that this step is the most important of all. Activation is tied directly to user experience. It refers to the amount of time before a user obtains value from your product.

A business with great activation will see the majority of users who sign up continue to use the product over the long term. Whereas a business with low levels of activation will have much lower rates of usage and retention over the long term (if at all).

A great example of a business with fantastic activation is duolingo. The core value of this website (learn a language) is demonstrated very quickly – literally within a few clicks you’re learning a new language. You don’t even have to sign up!

In this scenario, activation has been positioned before acquisition. Duolingo actually ‘activates you’ before they ‘acquire you’ (so clever). They have you sign up after you get to experience the value of the product. Ultimately, this means activation is 100% (a dream).

An easy way to start caring more about activation is to change your user acquisition metric from ‘number of sign-ups’ to ‘number of activated sign-ups’.

Retention

Growth is all about retention. Don’t bother trying to scale a product unless you have retention. It’s like trying to fill a bucket that has holes in it.

If you truly want to be an awesome growth marketer, please spend some time watching Alex’s presentation on growth. He is a former VP of marketing at Facebook and truly understands the power of retention.

Retention, put simply, is whether or not users come back to use your product a second or more time. What’s the point of acquiring new users and activating them if they’re just going to stop using your product? In terms of total users, it’s a lot easier to keep adding more users to your platform with a growing base, than trying to compensate for all the users who are disengaged and no longer using your product.

If you have low retention, you have big holes in your bucket (and activation is probably the main problem). In other words, when retention is down, it’s not the fact that people aren’t using your product over and over again, it’s usually because they’ve never used it, not once.

For those of you who are starting a business, retention is actually a great sign of product-market fit. If 40% of users are being retained, this says a lot about the value of your product. And in our experience, 40% is actually a good 30-day retention rate.

Retention metrics vary from business to business so it’s really important to consider how you’re going to measure retention. The simplest and certainly most common measurement of retention is monthly active users (MAUs).

A better (but more complex) approach is measuring the difference between the number of times a user used the product, compared to the number of times a user could or should have used the product over the typical time period in which a user should use the product.

In other words, when the user could have or should have used our product, did they?

E.G. When a user needed to book a flight, did they use our platform to do so?
To determine this ‘typical window of usage’ a social media site might be interested in weekly active users (WAUs), whereas an end-of-financial-year accounting platform might have to wait a year to find out if a user is retained.

In it’s early days, Facebook as a social media platform was heavily focused on Monthly Active Users (MAU’s) while other social platforms were mainly measuring total registered users. What’s the difference? Facebook cared more about people actually using the community, versus the number of people in it. Sounds like an awfully familiar homage to core value proposition doesn’t it.

To go further, Facebook had a golden rule for activation in their context of retention. They thought that if a user got to 10 friends in 14 days, they were much more likely to be retained as a user.

It’s important to be mindful of the difference between correlation and causation here though. A similar metric was espoused by the folks at Twitter: users with 20 or so followers were more likely to be engaged over the long term. This sounds like causation, meaning by following 20+ accounts it would cause a user to become engaged over the long term. To encourage/increase this, Twitter introduced a single button during on-boarding that automatically followed 20+ people. Effectively forcing activation.

A quick aside before we proceed, forcing activation never works. True activation involves the user doing the work, not the product ‘showing’ or ‘demonstrating’ or ‘stepping the user through’ the product.

Alas, Twitter’s observation of users who followed 20+ people being more engaged was actually correlation (not causation). Meaning people who were engaged also happened to follow 20+ people. In other words, one didn’t cause the other.

Revenue

This is pretty simple. Are people paying to use your product?

Yes = good.
No = bad.
Any questions?

If you’re a bit of a sucker for psychology like us, there is a lot of cool content out there on pricing, and how humans react to it. Hint: we as consumers make some very dumb decisions.

A cool example is the psychology of decoy pricing on popcorn. You’d be surprised how you can make this work for a range of business pricing decisions.

Referral

The last component of the SaaS funnel is referral. Have you heard of the phrase ‘net promoter score (NPS)’ before? It’s a great way to understand how likely your users are to refer your product to other people organically.

Companies can work out their NPS by asking their users “How likely are you to recommend this business to a friend or colleague?”

The reason why this metric is so important is because referrals are directly correlated to the virality of a product, and how much it will grow organically through word of mouth.

Companies such as Dropbox, PayPal and Uber have all used incentivised referrals as a catalyst for growth. Refer a friend and get $20 in Uber vouchers, or $20 into your PayPal account or even something as simple as 1GB extra storage in your Dropbox!

Incentivised referrals are great. But remember this:

What’s better than incentivised referrals? Inherent referrals, or inherent virality.

Inherent referrals are ones that come about because of the nature of your product or service. There may be a purposeful mechanism behind it, and it is built in to how people would normally experience or use your product. Sharing the product is part of everyday use.

Email and telephone calls, for example, are inherently viral. You can’t send an email without sending it to a recipient.

Inherent virality is so powerful, and if you can discover it, it will certainly be your biggest driver of growth. Consider this, which of the following referral features drove more growth in Dropbox?

• Incentivised referral: share Dropbox and get 1GB for every friend that signed up.
• Inherent referral: share this file/album with a friend.

Now consider which one of these two strategies is cheaper, and which one is the longest-lasting. Remember, it’s the long-term sustainable tactics that we want to identify and include in our Growth Machine.

A word of caution though. Be careful trying to engineer inherent virality in products that don’t inherently have it. Technically speaking, it is a very difficult test to run, and despite the many times we’ve personally tried to implement an inherent virality strategy, it’s almost never worked.

If you do want to do it though, and at least want to test it, ask yourself the following question: ‘where in my product experience would someone naturally share/communicate with another person?’. If you are able to really maximise this point of experience, you don’t need to try and convince users to tell their friends. They’ll want to do it anyway, all you’ll need to offer is the button/or link to enable them to do it. Even better, if your product by nature has a collaborative element to it, your inherent referral mechanism would also act as an ongoing activation (and therefore retention) factor.

e-Commerce Sales Funnel – The Ol’ Fashioned Way

A typical e-commerce website is transaction focused. It has browse, category, product, and checkout pages. eCommerce follows the following formula:

Improve any one of those three dimensions (without negatively effecting the others) and you will increase revenue.

While there is still a lot to this process, many modern e-commerce businesses adopt the SaaS mindset typically with the intention of outperforming rivals.

A site that adheres to the typical e-commerce way of life in Australia is Myer. Much of the site acts like a directory. They hope you click around, then find something that interests you enough to add it to your basket and ultimately convert.

An example of an e-commerce business, that has literally dominated every market it has entered because of its SaaS mindset is Amazon. Their focus on activation and retention is without doubt integrated into the core of their business.

A sure bet you can make about Amazon is that they will try and get as many Australians as possible to make one purchase from their platform. That way they’re signed up, can experience the value Amazon offers, and Amazon has a chance to ultimately retain them as a user.

This is an example of an e-commerce business thinking about activation. An example of Amazon thinking about retention was their introduction of Amazon Prime as a subscription service. This is a sure way to raise the customer lifetime value (CLV) of a user over time.

Over the years, eCommerce has become increasingly reliant on email and pricing as the value drivers in their marketing funnel.

High Consideration Sales Funnel

This funnel is quite similar to e-commerce but has a much longer purchasing lifecycle. This is largely due to the ‘high-consideration’ nature of what’s being purchased (cars, holidays, degrees). This funnel also accurately describes a sales funnel through to lead generation.

In a high-consideration environment, marketing teams will spend much more time in the awareness, interest and evaluation stages of the sales funnel.

Typical examples of products that would have a sales process like this online include enrolling in tertiary study, buying a property, purchasing a car, or booking an expensive holiday.

Few people have access to such large credit facilities that they can afford to purchase these items online. Think about the most expensive thing you have bought online. Maybe a plane ticket to Europe? Rarely would your average consumer spend more than $5k online.

What about a student’s university debt? The customer’s credit facility is actually the government, and you definitely apply for a degree online for most universities. But because it’s such a massive commitment, the mindset of the user will lend itself to the high consideration funnel more than the e-commerce funnel.

A somewhat obvious insight when thinking about your ‘bullseye’ framework for high consideration products is the potential power of high value content. A great strategy in these scenarios is to have well-developed, long form pieces of content for the early parts of your funnel.

The important thing about high-consideration sales is that a transactional approach (like e-Commerce) doesn’t work. The reality is that whether you like it or not, your user is going to go through most of these stages in the path to conversion.

It’s also very important to realise that if you’re not there during the first few stages (awareness, interest and evaluation), don’t expect to be in the game further down the funnel when the prospect is about to buy. Users aren’t going to just randomly show up to your site and purchase (unless your Apple).

In this process, content is truly king.

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