To be relevant, a Rewards Program must be tailored to a customer’s’ lifestyle. Unfortunately, traditional metrics are not enough.
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In this episode of People & Business Podcast, we talk with Alastair Simpson, Design Manager at Atlassian for JIRA and Bitbucket, and Isaac Lopez, Product Manager at Nearsoft. They shared their experiences on the concepts of Time to Value and the best practices for creating Rewards Programs.
Head of Design at Atlassian.
Alastair is currently Head of Design, Software Teams at Atlassian. He is an advocate of using design thinking methodologies to solve complex business problems. Previously, Alastair worked at global publishers Reed Business Information as well as a digital consultancy firm consulting to Qantas, FOXTEL and Telstra.
He also owns a rather large tee-shirt collection. You can find Alastair on Twitter at @alanstairs
Software Developer at Nearsoft.
Isaac has an agile and pragmatic approach to the development craft. He has created a wide variety of business applications, with a particular interest in web apps and databases for the Travel Industry.
He is also the leader of the Nearsoft Academy, a training program to help recent graduates become world-class software engineers. As their mentor he blends top of the line tech lessons with psychology, persuasion, influence, and economic educational techniques.
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[1:25 ] Alastair, at Atlassian you have developed the concept of time to value when creating experiences. Can you tell us what is it and why is it important?
Of course, Time to Value, it’s a really tricky thing to understand. And I should hat tip to one of my colleagues, Jay Rogers who is one of the researchers here at Atlassian. He kind of pointed me to this time to value concept.
Time to value for us means the time that it takes for a customer to actually realize and get true value out of our products and services.
So that time could be 30 seconds if they get something onto a board and actually start to get work done. Or it could take a bit longer depending on what their motivations are after signing up.
And as I said, it is a really tricky thing to understand but if you want to really grow your products and actually want to get that fast growth into your product growth rate, then you really need to understand that time to value equation for your customers. And for the different customer sets that may be coming to and using your product.
[2:31] I can see that it’s very important then to have the customer input into the equation and understanding those motivations.
In your case since you are very experienced in the travel industry, how important is it to know the motivations and the psychology of the customer when creating a rewards program?
Well it’s fundamental, although it seems obvious, a lot of companies forget that rewards programs should reward desirable customer behavior.
We should know, we must know how to make this program attractive to customers by understanding the customer needs and desires.
So from the customer’s perspective, there are at least five dimensions about how to know that a program is useful for our client or for our customer. And one of those for example is cash value or choice of redemptions. Or what is the value that the customer aspires?
Also you really want something convenient. And all of those dimensions are part of the motivations and psychology of the customer. So you should know at all times what is the behavior that you want to reward.
So that’s fundamental again.
[3:46] Maybe if I could jump in on a little story. Something that I found really interesting there from Isaac, you mentioned that one of the first things you need to understand is what is your customer need?
Obviously at Atlassian we don’t build travel products but I travel as a consumer and I travel for work. And I travelled to San Francisco to give a talk about time to value and about onboarding. And I travelled with my wife and my six month old daughter at the time.
And I sent off a few email inquiries to different places rather than just going through a standard booking.com site. And I sent off a few email inquiries and I did that because I had a specific need. But I didn’t raise that need initially in my email. I was just looking for quotes and then one place in San Francisco, a place called with bed and breakfast which speaking of loyalty programs, I’ve been back there about half a dozen times but this was the first time I had ever been. And they replied very quickly with a really sweet email and then they asked me a really key question like why are you coming to San Francisco?
And that helped them uncover the needs. And I said I was coming for work to speak at a conference but that I was also traveling with my wife and daughter.
That then allowed them to give me much more personal service. And they immediately replied and instead of offering me a standard bed and breakfast room, they offered me a small apartment underneath their main bed and breakfast house which was away from other guests.
So that meant that my six month old who was going to be really jetlagged after flying from Australia to America, wouldn’t wake up and disturb other guests at the bed and breakfast.
And then they also went a step farther and were like, do you need picking up from the airport with a car service that can offer a child seat?
So they understood my needs and they almost proactively understood that off the basis of one simple question of why are you coming and understanding my needs and motivations.
And as I said at the start of that story, immediately the time to value, I hadn’t even been there, I had just seen their website. But just off the basis of a couple of emails, the time to value that I had there was almost instant.
We need to focus on trying to deliver the best experience for the different types of people coming in.
[5:52] So it seems to me that time to value is something that must be owned. And at Atlassian how do you guys do this, is it time to value of your products assigned to somebody? How does this work for you?
So we generally have what we call funnel metrics. They are referred to loosely as “pirate metrics”, the double A, triple R funnel around acquisition, activation, retention, revenue etc.
And that funnel helps us divide up which part of that funnel is owned by which team. So acquisition clearly is owned by a team like Marketing for example. But we do have specific teams that look at getting customers activated within our product. So getting them to Time to Value.
So we do have specific teams that look at that part of the product journey for our customers because that’s quite specific, you have to understand for example in JIRA software sure it’s a software team coming in but are they a team that runs strict SCRUM? Do they run Kanban? Or are they just looking for a board that integrates with their developer tool.
And so there are different needs of that customer coming in. So from a product team perspective, the product team wants to build the best product experience holistically but then we need to understand new customers coming in and they have specific needs and we need to focus on trying to deliver the best experience for the different types of people coming in at the top of our funnel.
[7:40] That sounds like a lot of data that you have to process. So I wonder how do you in the travel industry gain that data? How do you pile it up? How do you gather it and how do you use it for creating rewards programs?
OK, so there are a lot of tools specifically for these SaaS providers. So I had the opportunity to work on a project for a client that’s called Switchfly. This client has a SaaS platform for the travel industry.
So they have this big project where American Express where they wanted to leverage all the American Express data points gathering and structure on all sites. They wanted to use it and be able to communicate all the data between all the sites and all the work, and also this SaaS platform.
So in that project,we use a tool that is called Omniture. So Omniture is a tracking or analytics company, or it was back in the day.
So we used this and it was interesting because we were interacting with several parts of all the American Express data tracking teams.
So there were some teams that were working on the customer behavior and purchasing, especially for tracking the behavior of each customer and what purchases. And on my side I worked on setting beacons for the user interaction on the page.
So we track everything like how the user searched, what are the selections?. And also when the user was about to be converted and make a booking. And we also track how many points or how many miles the user used on a given booking.
So the thing is it’s interesting how you can track almost everything that the user is doing on the site.
And the great part is not only tracking but these tools, for example Adobe Analytics, you can integrate other sources not only your web data or web tracking data, you can also marriage that info with the offline or the retail purchase of the customer.
So the thing is once you have all of that data, the real problem is how do you make simple reports or reports that give you insight to make decisions.
Data without insight is pretty much useless.
[10:08] Here I think that’s going to be a good jumping point. How do you think that we could use all of that global data to make decisions based on gut feelings. How do you imagine that Alastair?
I think the key thing for me is something I’ve learned in this role and also in previous roles, data without insight is pretty much useless in my opinion.
And so one of the things learned at previous jobs is we started collecting a ton of data and we’d instrument the products and we’d get loads of events. But then nobody had asked the question upfront around what problem are we trying to solve? Or what does success look like for our customer?
We were just collecting data with no real meaning or intent behind it. And so that data became almost useless and it became quite heavy in the product. And this was at a previous company.
That’s something that I try to work with the product managers and the analytics and the designers upfront before we do any instrumentation or before we try and get any data out. It’s like, what problem are we trying to solve here for our customers? What do we believe success looks like?
Then mapping the data points that we believe we need because we may find that we already have the events in the product that we actually need. It’s just a matter of extracting them and making them into a useful report and actually getting some insight and some meaning out of that data that you already have in your product.
Or maybe you do need to add some more instrumentation. But the key thing for me as a designer is to start upfront with the problem, with what you believe success looks like, and then working back from there and saying what do we actually need to get out of our product in order to be successful?
[12:10] Why are you asking this? Is data not enough? You mention about this gut feeling, why it’s important. And we saw that in one of your talks where you said gut feeling needs to be as well in place so that you can make better decisions.
I wonder for you, how do you make a relevant rewards program?
The thing is that the customers don’t want to play with 20 different options or waiting a lot of years just to get some gain about the program.
For example, I had this experience two weeks ago when I went to a local bookstore here in Mexico, something similar to Amazon that is called Gandhi.
So they have this reward program that they call Page One. And the thing is that they tell me, we have this program and if you want to buy this card, we’ll give you some points and we give you an opportunity to meet outdoors and a lot of things but you have to do a lot, at least for myself, it was really irrelevant all the actions that I had to do just to get some benefit from the program. I’m saying that even if I consume a lot of books.
So having to do a lot of things just to be part of that program is completely irrelevant for me. But that doesn’t make me really engaged with them.
The thing is how to make it relevant, it’s going back to the first question about the needs and what are the expectations, what the customer really values.
That is the important part, is just to know your customer, know what are their needs and try to find a way to give something back to him in relation to the value or the profit that you are getting for that customer.
AB tests are valuable allies and they help us understand and grow and optimize. But they aren’t a replacement for clear headed, strong decision making.
[14 :16] It seems there is a customer engagement problem there.
Alastair, you in your projects, do you measure this? So how can we measure engagement which is such a subjective response from the customer?
There is a really nice quote from Julie Zoo, who I am sure most people are familiar with, the Facebook product design director, and she dates, data and AB tests are valuable allies and they help us understand and grow and optimize. But they aren’t a replacement for clear headed, strong decision making.
So you mentioned that gut feeling and that intuition because I believe in data informed design. So taking quantitative data, qualitative insights and your intuition and your gut feeling.
But that’s why people get employed and why you become more senior in your roles because you get more experience and you screw things up. But all of those mistakes are helping me grow that intuition and that gut feeling and understand where I need to rely more heavily on data or more heavily or heavily on qualitative insights or more heavily on this is just best practice and this is how we should proceed.
And so it’s always a constant tradeoff. It’s always a hard thing to try and quantify and measure.
But I think if you take away that gut feeling, that intuition and that experience from people from individual contributors and designers and developers and engineers, then going to go too far to the other spectrum where you will not trust people to make decisions in your organizations without some piece of data that backs that up.
I think that’s really important.
And another point that I’m just wanted to talk about that Isaac was just talking about, about knowing which data points to kind of look at. And that’s something that we are looking at quite strongly here is how do you triangulate multiple pieces of data to give you a better sense of where you are going?
Because you could have one piece of data that says conversion has gone up and that might be great. But then another piece of data that says our NPS has gone down.
So conversions have gone up but people are actually not enjoying the product as much anymore.
So that might be OK for a little while. But if you let that keep going, then at some point your conversion will start coming down because people are actually hating your product more.
And you need to understand the two different points.
And again, an example from a former company, but we were running experiments to try and optimize a specific page. And we noticed some of these pages increased our revenue, essentially getting more click through on ads. But we also noticed that our customers were getting less click throughs and less emails and inquiries to their products and services.
So we could’ve just gone revenue is up, awesome, we are doing a great job and we are making more money. But if we left that, over time the customers that were actually using our service would’ve been more annoyed and probably less likely to stay with us.
So it’s super important to triangulate the different data points that you can get.
[17:18 ] Linking back to what Isaac is doing in the travel industry which is maximizing the engagement.
I wonder if in the case of a rewards program, are there certain recipes or things that we could follow to make sure that we are in the right way?
There are like five rules about how you can make a good rewards system. And one of those is that you should consider that all customers are not created equal. And you should consider on the design of your program that the value created must exceed the cost of the value delivered to the customer.
So you should as a business, you should get more than what you are rewarding the customer otherwise it’s not going to be a business. So you always have to be aware of that.
The other part that you should consider to maximize the customer engagement is the customer behavior should drive value sharing. All the parties involved should be getting some value and that value should be shared between the customer and the business or all three parties… there should always be some value shared.
The other part is when you are designing this kind of loyalty programs or loyalty implementation, is that the long-term perspective is really critical otherwise you are going to end up with the classical discounts programs where you run discounts for a given season. But that doesn’t provide the loyalty or it doesn’t provide the going back to the business.
And the last but not least is the offers, whatever you’re giving to the customer should be attractive to the customer, it should be something that they want.
So having those in place, it’s very difficult if the loyalty program doesn’t have the engagement that is needed to be profitable and also producing the right behavior from the customers.
Focus on the job and getting your customer to actual value in your product.
[19:26] Let me think this through because you are mentioning those are five guidelines that you can follow to make an effective rewards program.
But in the case of enterprise products such as those offered by Atlassian, do you guys follow a principle as well? Or how do you guys identify the core feature, the core value that you are providing per instance for JIRA or Confluence or what not?
That’s something that we’ve talked a lot about lately and we always come back to the customer. And to be honest different teams will have slightly different frameworks about how they do that internally. But certainly one that many teams are following is the jobs to be done framework.
So what is the core job that your customer is actually coming to do at your product? And essentially they aren’t coming to navigate or to search in Confluence etc. They are coming to create something and get work done across the board and map that to their existing workflow.
That’s what they are trying to get done.
So certainly a framework that we use is that jobs to be done which Intercom have done a really great job of documenting.
But as I said, different teams use different frameworks. But that’s certainly a popular one that people use.
It drives back to where we started in this conversation, what is that customer need? What are they really trying to get done here?
Because coming back to time to value, a customer really doesn’t want to setup anything. That’s not why they are using your tool. That’s not why they came there, to go through an onboarding flow.
And again, Sam on User on Board, does a good job of talking about different onboarding flows in consumer and enterprise products. But focus on the job and getting your customer to actual value in your product.
And that’s something that’s really hard, especially in consumer tools, many consumers have different wants and different needs.
And in enterprise tools, like JIRA software software is a good example, some teams are a small team of five and they just want a lose Kanban.
Some people using strict SCRUM software are 10,000 people companies and they’ve got massive teams and they want really strict SCRUM. But other teams in there want Kanban.
Atlassian is a good example of that. Different teams within Atlassian use variants of SCRUM and Kanban depending on what works for their team and the project that they are working on. But it’s all around agile.
So really trying to understand the core jobs and then getting people to value fast is tricky.