For some time, Contextual has had the ability to track pages visited and (on some plans) clicks.
We’ve also allowed Product Teams to see a user’s targeting with Tips, Tours, Tooltips and Popups. We’ve taken this one step further and allow you to see a users sessions and what they click on within a specific session – you can also see WHEN they interact with the guide content you’ve targeted for them.
Above you can see the user “William Gibson” in Session 1, visited particular screens and was presented with a Carousel – their engagement was to interact “accepted” rather than dismiss it.
Dashboard user can click into any user and like a CRM can see each individual’s:
a) their device (phone, tablet, iPad, web browser)
b) how many sessions, when they installed, last user.
c) experiments and how the user engaged
d) select from a drop-down of sessions (as seen above)
e) Custom Tags (attributes) to target, personalize, segment or add to an audience. For example, a tag called JobRole could be synced with your App to be able to target “Project Managers” or “Sales Team” for specific guides.
These two examples illustrate how you can drill down to any user and see which guides they’ve seen and how they responded. The first user “Rejected” and “Touch Out”, the second user “Accepted” the guides.
This is a per user version of the Guide Analytics that visible when tracking the performance of any content you have created.
In the upcoming full interview with Deputy.com‘s Growth team leads (Francois Bondiguel – Head of Growth and Jordan Lewis – Director of Growth) we cover a lot of great Onboarding/Growth experiences and ideas.
But I’ve clipped this onboarding gamification example for special attention – its the most genius growth hack you’re are going to see this week!
(to make sure you get notified when I publish the full interview, add your email in the sidebar on the right –>
B2B SaaS Trials
In B2B SaaS its super-common for the prospect to ask for an extension for their trial.
At Contextual we get this all the time because whilst the Product Manager loves what they see, they need to schedule developers to integrate the mobile SDK’s – so our 14 day trial is sometimes too short.
Deputy recognized this as a reality of their business and their customer success so they flipped it on its head and allowed customers to self-service their trial extension by performing onboarding tasks.
Lets hear what Jordan and Francois have to say:
Specific Activities that get an extension
This video covers what are the goals that Deputy want their prospective customers to achieve. For example, getting on a screenshare call is a reliable predictor or trialler –> paid customer.
The extension activities are:
Add your Business Name and details. Gives you 6 days.
Book a screenshare
Setup your mobile number and install the mobile App. Earns 2 days.
Add your employees for 5 extra days.
Once you’ve published a shift more free days will be unlocked
Approve a timesheet to unlock free days
Choosing your plan allows you to keep your free days.
The next video digs in and shows you the type of dialog and carousel content they show the user to explain and encourage.
Growth is iteration
Finally Jordan mentions at the end of the video the number of times they have iterated this flow – have a listen you will be surprised!
Tools like Contextual allow you to iterate quickly with some of this content without disrupting the product roadmap, not all things can be done “no-code” but a lot of experiments can be tested, measured to see what is working the best!
Aligned goals
This is a great example about thinking about the customers goals and recognizing the overlap with the Product/Growth teams goals. As I discussed in the post “Goals, Segments, User Activation” don’t prioritize yours goals above the user’s goals. They have a JTBD and that is what will drive activation and retention!
In the Part 1, we covered the importance of establishing goals around your engagement experiments and flows.
We could call this Part 2: “Segments are nice, Segments are dumb”.
Segmentation will eventually be “individualization” – we cover the steps needed to get there. Thinking in “Goals” are an important step.
Since Contextual’s inception, we provide default segments useful for tracking and grouping users. Names like Newbies, Light Users, Power Users, Churning, Zombies have filters for capturing generic “buckets” of users.
In addition, you can choose a combination of filters based on your own Custom Segments. This example below is creating a segment of “Recently active Project Managers”.Contextual
Once having defined and saved the “Active Project Managers” segment, your Product Team can then:
target tips, tours, flows, popups at this group (in conjunction with other triggers)
track the size and membership of that segment.
This is a very good granular way at looking at your user base and targeting flows and content that is customized for their job role.
But…
User’s don’t care about your segments.
Ask a user what segment they are in. You’ll get a blank look.
Segments ignore the needs hopes and wishes of each individual user. A segment aggregates and abstracts them into a “label”.
But each user is on their own unique journey and within a segment you should be seeking to personalise and respond to individual needs at scale. How do you scale for each unique snowflake?
Credit: Monty Python, Life of Bryan.
Scaling Individualization
If you have 25K Monthly Active Users, then having 6 segments is easy for you to manage but mediocre for users.
One solution would be to create more segments – the ultimate solution would be to create as many segments as there are Users (25,000 segments!). That would be:
ridiculous!
a huge amount of work for the product team
always out of date.
Still not what a user wants from your product.
Artificial Intelligence will eventually make this possible: what Netflix does for movie recommendations or Facebook does in your feed. More on this later.
Goals – a user’s needs
Better than structuring your users into segments – goals align the Product Team’s interests with the user’s interests.
Its not very different but an important way of thinking about your user’s needs.
Example:
Already you can see a business GOAL or event looks like a customer progression in their own journey, there are some mandatory steps in the business process that each user must be aware of and complete:
DETAILS_FILED = YES, NO
TERMS_AGREED = YES, NO
QUOTE_CREATED = YES, NO
SALE = YES, NO
Then joining these journey goals with Contextual’s seamless tracking of the user’s behaviour, e.g:
Install date and time
Usage dates and times
Screen Visits, Session count, length etc
Touch events
Delivers a rich pool of rule-based or training data that can tell you more about the user that enriches data-driven segment toward goals and “individualisation”.
Today, by manually working backwards from the population who have achieved goals you can determine the “Next Best” segments you should be targeting. Contextual allows you to “what-if” audience size my testing goal-completers with other data. You could export or dump this data to a datalake (redshift, bigquery/bigtable, snowflake, Azure DW) or data-mining system for better tools for PCA and to seperate causality from correlation. Then you can compare goal-completer’s rows vs not.
You should end up with some observations like:
“80% of users who completed the introduction tour” resulted in DETAILS_FILED=YES”
“90% of users who completed the introduction tour” within 24 hours of registration resulted in DETAILS_FILED=YES”
The goal at scale
The interesting thing about goals is that unlike the 25,000 potential segments, there is a small number of goals that matter in the sequence of a user journey – so scaling with the above method is naturally a more manageable.
But…let’s face it, you don’t want to click through all your users to uncover nuances submerged in the data that lead to greater personalisation and individual needs.
DETAILS_FILED = YES is an important business goal in this app – the business relationship is established. The Product Team can learn a lot from what attributes distinguish these users from the DETAILS_FILED = NO users. There are also other filters that are pre-cursors, for example, users who have churned will automatically DOCUMENT_UPLOADED = NO.
From the Contextual data we can learn that these 2 goal based segments can be broken into (we chose) approximately 10 interesting segments.
For example, we know that users who viewed the “Completing the Document” tip tour have a higher success rate of DOCUMENT_UPLOADED = YES.
So one logical conclusion would be to keep re-showing this tour to users until they complete it. Another action could be to trigger a feedback question to these users.
Some other attributes are surprising – for example Android uploads from newer devices is a predictor of success. How the hell could the Product Team manually discovered that? The action is the Product Manager can schedule an investigation by developers to find a root cause.
Individualization with Machine Learning
Each of the 25,000 user’s journeys is describable by the data (behavioural, segmentation, goal, external enrichment).
Instead of the manual iterations above, you will see AI in platforms like Contextual by training on the “goal data” (supervised) to learn the models, then automate interaction with new users as they move through the journey.
The challenge is that both platforms and Product Teams outside silicon valley are not quite up to the task at the moment. So, purchasing decisions for on-boarding/engagement products are made without this as even a consideration, so we need to user the rule method and engines like Contextual to get results today.
Keep an eye out for companies like https://www.clearbrain.com/ who are early but pitching causal based analytics to convert customers.
This multipart series covers best practice for activating user’s on their journey. “Activation” has a specific meaning, the way it was defined in McClure’s Pirate Metrics – if you are not familiar with this, take a scan of this post.
In this post, we cover UX goals you want YOUR user’s to achieve. The next post will compare with segments. Contextual allows you to add segments from the beginning which is great, but segments also have problems that we’ll dive into.
Setting meaningful user goals
All app owners want to get their users to the “AHA” moment as quickly as possible – this increases engagement and “AHA” is an ACTIVATION event.
The problem is that many App owners don’t know what that means in their App:
There is not enough granularity of data to know.
New Apps have little or scarce data.
The bigger problem is that the goals are too big (not granular enough) – “convert triallers to subscribers” is not a goal, its a wish!
Work Backwards from goals to design
Steven Covey (of 7 habits fame) says “Begin with the end in mind”.
Often Product Teams visualize how they want to guide the user in the App. Implicitly the goal is embedded in the design discussions but quickly gets buried with the design’s colours, shapes, wording, validation logic. Its just human nature.
Instead we suggest to always keep goals at the center of design.
At Contextual we use Atlassian’s Confluence for writing the requirements docs and in the sample templates they have “Goal” and “Metric”.
They are encouraging a Product Manager to not just define User Stories but also “what does success look like”.
Above is an example from a Contextual Requirements doc. In this Confluence template the Metric column is encouraging a QUANTITATIVE measure for a GOAL.
This is awesome because the whole team can focus on what is the important business result. A better “Metric” for
"Customers can integrate with reduced support ticket load"
could be
"Reduce Integration related support tickets by 20%".
Note that it has nothing to do with how the product looks and all about the cost to the business and happiness of customers.
Make goals granular
In FULL SCALE***, Richardson says:
“Determine goals, milestones and priorities. These three tasks make people more productive. Productivity makes better use of your time. Time is directly related to growth. Growth is why we’re here. Therefore, growth is goals, milestones and priorities.”
Your goals might be too big and too abstract. For example:
"Reduce Integration related support tickets by 20%".
or
Increase conversion to paid by 30%
are desirable business goals but don’t map to a user in their journey.
So you need to map and align the user goals. Break the business goals into multiple user behaviours in your App. This might simply be a “BUY” or “PAY” button in the App but the following Pandora example breaks “activation” into 3 user behaviours that you would define as goals.
Example User Goals
The first step is to understand what your successful user journeys are. A famous example from Facebook was “if a user gets 7 friends in 10 days they will be a lifetime user”.
Three other examples are:
1. Pandora: I recall a speaker from Pandora explaining that an “activated” user was someone who had:
Played songs
Invited a friend
Saved a playlist
You can think of these as more granular goals.
2. Checklists and gamification. LinkedIn mission needs great profile data. They did an incredible job of getting people to update.
3. Spotify – the lead data scientist at Spotify told me: their top-tier users, the most engaged people, actually treated the application like an operating system. The data science team would analyse their behaviour and then map journeys for other users that made it easier to become top-tier.
In Summary: you need to create goals that you are able to measure that are meaningful to each user’s journey.
About now, you might be looking liking like this.
This is where your personal knowledge of your App is essential.
With your team:
break down your big (business) goals into smaller events you’ve seen. For example user behaviours like:
a user bookmarks an item that shows they have commitment.
If they hit the payment page but didn’t complete thats significant.
In the next post, we will discuss data-mining as a possible method of surfacing goals. If your team or tools have that, this is ideal.
your analytics platform. You may not have a team of engineers, data scientists and PH.D’s that LinkedIn and Spotify have but it’s likely you are already using analytics tools. It may not have a magical answer but you can do some “what-ifs” around user behaviour.
User Click activity can be a quantitative goal
On some Contextual plans you get click/touch tracking**. So looking back 30 days for a question like “did a user touch/click BUY button?” could become a very useful goal.
There is a very good chance that a “click buy button” is exactly the behaviour you want to measure and 30 days history can be measured before and after you run a goal-based experiment. Outcome
You want define a “happy user journey” with granularity like Pandora. Here is some examples:
“We know 60% of users who don’t churn and Visit X page and Search for Y getting a successful result and Save an item become subscribers.
Users with Saved items are 60% more likely to make a purchase.
NOW you have a list of more granular goals.
In Contextual you can select goals based on:
1. Business Goals (the Custom Tag option above). In the Pandora example this could be the “Invite a Friend” process or the “Save Playlist” event. In other App is could be a purchase, getting an anonymous user to register an account etc.
2. Behavioural (Button Clicks, Page Views, or other InApp metrics in “Contextual Tags” like Session Counts, Upgrading to the latest App etc)
In this example from Wikipedia, to set a goal to measure people who registered – you simply mouse over the “JOIN WIKIPEDIA” button and clicks/touches on that will be selected as your goal.
Iterate your process
Because this post focusses on goals and segments, I won’t revisit creating user onboarding activities. Sometimes this is code design and sometimes its using a tool like Contextual to create walkthroughs. To see some examples of what Contextual can do to help onboard users or help guide them to discover and use new features, check theseposts.
Create flows/walkthroughs/tips etc to test your hypothesis
Measure the results. For example did the “BUY” button clicks relatively increase? Go back to the Contextual “Metric History” analytics chart (an example above). Can you quantitatively measure uplift on user interaction with your “BUY” button?
Refine or discard your hypothesis.
Repeat
In addition to analytics of Metric History, Contextual’s experiment analytics allow A/B splits against goal to prove/disprove hypothesis. Two detailed posts cover thistopic.
Next Post: Segmentation
Now that we have Goals defined in a granular and quantitative way, the next post will cover the pros and cons of segmentation and individual user journeys. Where is personalisation practical? If you want to be notified signup on the side-bar 🙂
Notes
** Contextual doesn’t try to replace dedicated analytics products but touch/click behavioural analytics are designed for Product, Customer Success and Growth teams to see the impact of tips and tours.
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