Watch: Diving into 2020 Mobile App Engagement Benchmarks
Watch our latest webinar where Robi Ganguly, Apptentive CEO and Co-founder, and Christy Culp, Apptentive VP of Customer Success, share exclusive data and key insights from our 2020 Mobile App Engagement Benchmark Report. Since the report is an extensive resource, this webinar serves as a valuable synopsis where we walk through the data and highlight key takeaways for our research.
This data serves as a benchmark for brands with mobile apps in the Finance, Travel, Food and Beverage, Retail and Shopping, Lifestyle, and Media categories.
We discuss mobile engagement data specifically in the following categories:
- Sentiment analysis
- Customer retention and loyalty
- Ratings and reviews
- Interaction and response rates
Robi: Well, hi everybody. Good morning, good afternoon or whatever time zone is out there. We’re going to have our video on during this to try so you can see our faces, our expressions. As noted in the chat, we’ve got a Q&A section. If you hit that button, you can ask us questions. I will try to interact with those questions towards the end. But along the way, we might pause and dive in a little bit. We’re trying to experiment a little bit with the formats. I’m sure a lot of you are sitting in front of screens a lot, so, we’re going to mess around a little bit with trying to engage you a bit better. But what are we here to talk about? We’re here to talk about our benchmark reports. And, you know, this is really, for Christy and I, the fifth time we’ve done this. So, I’m co-founder, CEO of Apptentive. I founded the company nine years ago. We’ve been super focused on listening to customers for years and my colleague, Christy, has been with us for a long time as the head of customer success. Hi, Christy.
Christy: Hi, thank you so much.
Robi: Christy and I are going to share a bunch of information that we’ve gotten over the past year. And the information here is really, really important right now because what we do is we help companies listen to their customers and more than ever listen to the customers to help you through what’s going on. The uncertainty of today is predicated on not knowing really what your customers are thinking or what they’re feeling. So, it’s more important than ever before. And I really want to put a stamp here. As we think about these benchmarks, one of the things that we know at Apptentive and our customers know is you can listen to a lot more customers than your expectations have been up until today, right? Like, it’s not enough anymore to listen to 1 percent of your audience or to have 10 percent response rates.
You need to be thinking about how you get to 30 percent of your audience and understanding what the majority of your customers need is really cool. And we provide these benchmarks really to help people understand what’s going on. In digital, it’s still early days in terms of thinking about what is acceptable. And benchmarks help our customers and people, in general, navigate as if they’re in the sea and they don’t know exactly what their bearings are. So, they’re looking up to the stars and using them to navigate. And today’s seas are really rather choppy. So, it’s more important than ever before, we think, to navigate. And we have really a lot of this data pulled together in order to help you understand what the baselines are on app engagement and what the expectations you can have for hearing from your customers are. So, if inside of your organization people say, “Oh, we do NPS,” or, “We have CX service,” but you know that it’s only coming from 1 percent of your customers if you know your response rates are 7 percent, part of what we’re doing is helping you have a yardstick to understand whether or not you’re doing the right things and you’re hearing from enough people.
Because fundamentally, you need more information, not less, and you have to be able to make the case internally around ways in order to increase that amount of information. Now, why do we feel very strongly about our data? And we think this is really important, but we’ve taken this from over 800 apps and almost a billion consumers over the last year, and we’ve done this with our customers in the food and drink category, shopping, travel, finance, media, and lifestyle. So, we have a large coverage from a lot of human beings over a 12-month period and this is our fifth year of doing it. So, we have a lot of confidence that what we’re seeing is possible for you too.
If you’re not hearing from a quarter of your audience and you think you can get there, and there’s some really important tips and tricks that we’re going to share around that, and if you’re paying attention during this, you’re gonna also pick up on a bunch of the companies that we’re working with that are doing some amazing things. So, I urge you to pay attention to some of the stories I share around this because this is not theoretical. This is possible. You can hear from large number of your customers in order to predict what’s going to go on. So, let’s just jump right in. We’re going to talk about some of the general benchmarks that we have, and we’re gonna talk about something that’s really, really important right now in particular, which is customer sentiment. How do people feel?
Now, customer sentiment can be measured in a lot of ways. I want to define this in some of the ways that we’re going to be talking about this for the next couple of minutes. We have something we call the love dialogue. The love dialogue has been asked of almost a billion consumers in the past several years. And on average, 94 percent of people who were asked this question answer it. It’s a little bit higher on iOS, and 97 percent of people on iOS. And they had answered the question versus on an Android it was 87 percent, but we have a lot of confidence just around this measure because we know it’s not biased. When so many people are answering it, it’s really, really indicative of what’s going on. And we also know something that surprises a lot of people, which is that when we ask this question in front of consumers in their experiences on the web or in a mobile app, about 64 percent of those people actually respond yes, that they love the experience they’re having, they love the brand that they’re dealing with.
And this shocks a lot of folks because we tend to have a negative view because a lot of the feedback we get is really representative of a vocal minority. And what we’re talking about here is how to unlock really the silent majority, more of your customers. And when you unlock more of those customers’ voices, what we tend to hear is two-thirds of people are mostly really big fans. That’s why they’re there in the digital experiences in the first place. Now, again, there are differences between the platforms. We see a higher low percentage on Android than we do on iOS. For the purposes of this, we don’t think that that’s as relevant, but we want to be really clear with you. There are some deltas that we see, so this is the baseline of how we’re measuring and what we’re seeing.
But let’s get into this a little bit deeper because it’s not enough to ask this question just once. What we are able to do, because we are embedded in the experiences that are digital, is we’re able to understand how customers feel multiple times. So, what this is showing to you is a little bit more of the breakdown of how to think about customer sentiment. It’s an evolving feeling. How I felt yesterday is not necessarily how I feel today. Christy, how did you feel yesterday? We had a board meeting yesterday. How did you feel?
Christy: I felt nervous.
Robi: Nervous, and how are you feeling today?
Christy: Today, I feel great.
Robi: Fantastic. Right? So, that’s how humans are. That’s how we as people are. It changes over time. And what you’re seeing here is that when we hear from people based upon if it’s the first time or it’s multiple times, things will change. And what we’ve learned is that on a regular basis, about 60 percent of people are saying that they are fans either because it’s the first time you’ve asked them the question and they said, “Yes, I love this,” or they’re fans because they’ve answered this question multiple times and they’re repeat fans. That’s really powerful because repeat fans coming back on a regular basis and having a great experience is really important. That’s kind of what you’re trying to engender. We think every brand is aspiring to have customer love and this is what love looks like.
On the flip side, down at the bottom, what we’re seeing is that somewhere on the order of 5 percent of people were fans and then they’re shifting to risks, right? And when we hear that, man, that’s alarm bells because you’re saying that somebody was really having a great opportunity to connect with you, that they had a great interaction. And then 5 percent of those people on average are actually shifting to risk the next time you ask that question. It’s a huge opportunity. And the differences here between 5 percent and 3 percent specifically here on iOS and Android at risk is not just a small 2 percent difference. It’s a 2 percent difference every month. You see this shift every month. We’ll get into this in a little bit more detail. But the picture I want to paint for you is, overall, people’s feelings change. It’s really important to measure that. And on average, we see on a monthly basis about 5 percent of customers shifting the risk and about 4 percent of customers shifting from risk back to fair. So, there’s a loss there and we’re going to go into some of the ways in which to take action around that.
How you gauge these sentiment shifts is really, really important. So, when we’re talking about this, a lot of the things that we assume to be true and what we think hopefully is true for you and your listening mechanisms is that you’re connecting it to first-party data. And when I say that, we’re connecting it to first-party data at the individual level, what I really mean is that if Christy was nervous yesterday and happy today, that your systems are allowing you not only to capture that Christy said that, but then it’s Christy saying that, that you’re connecting your user ID level information with that voice of customer information in order to actually track that specific customer’s experience with you. That’s a must. As we’re talking about a bunch of the things that we go through today, you have to be thinking about are our systems capable of attaching that information.
And then you can graduate to the next step of tracking that shift so that we can see, “Hey, Christy has changed her opinion. Robi is actually really happy. What’s wrong with him? He’s happy all the time,” but it’s just me. I’m an optimist. Those things are really, really important to change or understand over time. And the way that this work, to kind of give you a visual, is that if, for example, you’re one of the 18 million people who use the Starbucks mobile app to order a coffee and then pick it up, when you’re asked that question a month ago, 10 days ago, and 3 days ago, you’ve had different answers. And so for example, you know, in this scenario what we’ve got is a customer who might’ve been asked this question three months ago, super happy a month ago, really happy, and then 10 days ago maybe not as happy.
And when you connected to customer ID, these are the sorts of pictures you can have an aggregate for a group of customers, but down to the individual is where this is really super powerful because you can also be asking this customer questions. Why did your sentiment change? What is happening? What’s driving that shift for you? Because this customer might be unhappy because their local store is shut down, and due to COVID-19 they’re not able to visit. That’s understood or they might be unhappy because picking up their drink was a real hassle at the store they went to because the store was not doing a great job. A totally different problem. Understanding of that customer level and understanding that shift over time, really, really powerful. I want to talk you through a story. As I mentioned, we’re going to talk to a bunch of customer stories though to put this into context around how people are using this.
When you’re able to talk to a lot of customers, what you’re able to do in your dashboard at Apptentive or with any system that is connecting this first-party data and identifying shifts over time, you should be able to get a chart, a chart on a daily basis that actually tells you a summary of the customers are shifting to fans for main risk and those who’ve shifted from fans to risks and an overall assessment of your volume on a daily basis. Really, really powerful. If you imagine being in a global consumer brand that has retail locations all around the world, tracking this at the country level, at the regional level, and even the store level can be really, really powerful. So, we were sharing this with one of our customers, and as we were walking through this and explaining the concept, I said, “Man, this is really great,” but they started to focus in on a specific area and it surprised us.
What they focused on were actually just the risk. So, as I mentioned upfront, about 5 percent of customers every month are shifting the risk. This is where our customer is spending a lot of time. They’re saying, “This curve looks really familiar. I’m really concerned and curious about why these people shifted the risk. I want to try and keep them. What’s going on?” And the more they spend time with it, the more they started drawing curves around what this looked like. And they said, “This actually looks pretty familiar to us.” So, they brought up some other data and then walked us through it. And what they discovered eventually was that if you time-shifted this data out by a couple of weeks, the curve was almost the same as their churn customer curves. So, what they came to the conclusion along with us was this data was an early signal of customers saying, “Yep, I’m not happy,” which then predicted a couple weeks later that they were going to churn and they were not going to come back to the digital experience. They were not coming back to order, which gets really expensive. And so, this is the first thing that we learned with our customers. When you track this over time, you can start to predict churn and actually get a customer to tell you before they churn that they are really at risk.
So, let’s move into a little bit more of a deep dive into retention, which is really, really important from the bottom-line perspective. Why is this? Well, all of you are basically on a journey to keep customers for life. As much as possible, you want to create an emotional connection with the customers. You want to service and help them in a really meaningful way. And so, customers will start out with you in a neutral place, right? They’ll make a purchase. They’ll download your app.
They go into your store. It’s like, well, not today. But, in general, they might have like a first or second interaction with you and they’re sort of neutral. But they could go two ways. They could either fall into the churn bucket because they don’t have a great experience, not interacted with, or they can start to get happier and graduate to a place where they’re a superfan. And superfans do things like grow your business by telling others about it. That’s a really, really powerful place for you to supercharge your base and grow it. This whole thing maps out as retention, right? You see people who start to use you more often, who rely upon you come back every month, every week, every day. That’s what retention fundamentally is now. And we know in mobile apps across categories, 90-day retention is 20 percent to 30 percent.
It’s pretty low, right? People have talked for years about how expensive it is to keep a customer because you acquire a hundred customers and then after 90 days, you got 30 of them left. So what we’ve learned around this is this is the overall scenario, but when you start talking to customers, you can change this by actually reaching out to customers and understanding how they’re feeling. Just the act of listening to people allows you to boost retention. So, this is another benchmark that we really highlight for our customers, which is just taking action to talk to more customers. Not 1 percent, but 25 percent, 30 percent leads to higher retention overall. On average, a tenth of customers see 90-day retention, 70 percent higher than the average mobile app. And this is really attributable just to the active listening, just showing up saying, “How are you doing?”
Not with a push notification saying, “Buy this new thing and here’s an offer.” It’s just that question of, “How are you doing?” So that’s really important. We think it’s really valuable to understand that, that alone is an opportunity for you to get better until you increase your retention. Now, let’s go a little bit deeper into some of the interactions that we see and think about this on an annual basis because some of you might be in industries where people don’t use the app every month or every day. They use it quarterly, maybe twice a year. It’s a big shopping ticket like the purchase is a really big-ticket item, so I’m not really in your app that much, but when I am, I’m spending a lot.
What we’ve also found is by tracking over the course of the year by using our love dialogue, people stick around for a lot longer, right? That emotional connection, understanding how people are feeling, actually changes their behavior in such a meaningful way that we see 67 percent of customers still around at the end of the year. If we talked to them at the beginning of the year, we still see them at the end of the year. And I want to bring this back to that point I was making about tracking at the individual level. If your systems are not allowing you to track at the individual level, it’s very hard to calculate this retention number. This is, again, when you start connecting the dots in this way and being really personnel, you can see what’s happening with behavior. And what we’ve learned is 67 percent more customers stick around a year later because they’ve been asked a question about how they’re doing. Really, really powerful stuff. So, that’s just the basic premise of thinking about retention, average of retention, and increase in retention from the perspective of understanding your customer sentiment.
But another thing that we’ve learned is getting out in front of customers, asking them their opinion, and then taking them on a journey based upon what they’ve said is a really, really powerful way to learn. And it shows us something really pretty neat. So, one of our big customers is a global media organization. They produce content and distribute it through apps around the world. And what they wanted to find out was not just who loved them and who didn’t, and being able to track those people over time, they also wanted to understand what the distinguishing factors were. And along the way, what we learned with them, in addition to really helpful feedback that helped them change their roadmap and serve personalized offerings, was that people who said that they love the app were actually a lot more likely to answer questions about what else they should be doing.
This company chose to take customers who had answered yes, and instead of just logging that information and saving it for later, immediately say, “Great. We’re super, super glad that you love us. Tell us why. Tell us what’s going on. Give us some information.” Two-thirds of the people completed that survey and told the company what was going on. Now, half of the folks who actually completed the no feedback survey when they weren’t having a great time, which is great, were huge fans. But what we learned around this that your fans have a lot to share. And if you open up the opportunity to listen to them, they’re going to tell you a lot about what you’re doing really well and potentially even where you can go in the future. So, that’s a really powerful benchmark as well as I understand that your fans do want to give. They want to give you love. They want you to give you information.
So, what can you do now to boost retention? So, the first thing is there’s a silent majority. For most of you, you’re really good at listening to the vocal minority, the people who show up in your app store reviews with nasty things, the people who show up on social media. But the key is to talk to those 99 percent who are not going to raise their hands, to get out in front of them. By doing that, just by doing that, you’ll see 70 percent higher retention in 90 days and 67 percent higher retention over the course of a year. The second thing is use it to predict and prevent churn. So, if you can identify somebody like our customer did before they churn because they’ve said, “No, I’m not having a great time,” then you can understand how to solve the problem and actually keep them. So, that’s another way to take action to boost that retention. Now, we’re going to transition into something really specific to app space and Christy is going to talk about ratings and reviews.
Christy: Great. Thanks, Robi. Just a reminder for anybody who did join a little bit later, we would love to answer some questions should we have time at the end of this webinar. And to do so, you just need to click the Q&A little button at the bottom of the webinar, and you’ll be able to submit questions directly to us. I just want to make sure. That’s a little different than what we’ve done in previous webinars. So for anybody joining, we want to make sure we can hear your voice. All right. So, let me get into ratings and reviews. So, Robi talked about some ways to talk to your customers who have had a good or a bad experience and to ask them to give you feedback. We have another way to do that, particularly with customers who are having a good experience. We would love for you to ask them to go and spend some time rating your app. So, in 2019 we actually saw a huge jump in reviews for both iOS and Android, both of the median and the average number of reviews per app. And this was actually particularly noticed [inaudible 00:19:06] where we had previously seen a reduction in volume after the release of iOS 11.
If anybody remembers that about a year and a half ago, iOS or Apple released the ability to do in-app ratings prompts. And those actually feel like they are finished when somebody gives you a rating. So, they click a number or click a number of stars and then they feel like they’re done with the interaction. They feel like they’ve given you all that they need. So, for a while, we actually saw a reduction in the average number of reviews in iOS. What’s really substantial about what we saw in 2019 is we did see a big jump in these numbers again. So what that means to us is we’re really thrilled that our customers are cracking the code about talking to the right customers at the right time.
What you want to make sure of before you’re asking somebody to go and leave a review of your app is that they’ve had ample time to experience the app so that they actually have something to say, they have a connection to you, and really have a place to give them meaningful feedback and have something to say in that. So, that is the most notable thing about reviews for 2019. And now, I will move into app ratings. So, for 2019, the text calls us out says it, but we also saw a big jump in the ratings per app in 2019, 158 percent in iOS and 44 percent in Android. Part of this is due to the continued adoption of the iOS rating prompt for iOS and understanding the rules that Apple has put in place. So, with the invention of the in-app rating prompt, they said, “You can only ask people to rate up to three times a year.” And it took a little while to understand what the cadence of those three times per year meant. But obviously, with the jump at iOS ratings, we’ve seen people take hold of that. And as I mentioned on the previous slide, in both iOS and Android, we’re really starting to see our customers, in particular, understanding what it means to talk to the right person when they’ve had the right experience. And we definitely attribute that jump in number of star ratings to that.
And then distribution of star ratings. Along with the higher number of star ratings, we’re also seeing a higher percentage of five-star ratings, which is a key factor we look at. We obviously…if you’re asking somebody to take the time to go and rate you, we want them to rate you well. At a higher volume of ratings, but a sign of a lower average star rating would actually mean that you’re just being noisy to customers. You’re not talking to the right people. You’re basically talking to them at the time that isn’t appropriate to them. You’re talking to them out of context. But when we see a higher volume of ratings, along with that higher star distribution, we know you’re asking the right people to give you that rating. And also, probably you’re improving your app over time.
And then I do want to tell just a quick story about what ratings changes look like using Apptentive because this is such a big value prop that a lot of people like to use us for. So in this case, we have a large U.S. bank who wanted to work with us and actually signed a contract with us, but took almost a year to actually get going live with us. Now, let me preface by saying our SDK is very easy to use if you’re not a customer. If you told me you wanted to go live tomorrow and you had some engineering time today, I would feel fine with that. This customer in particular just had a hard time prioritizing that engineering work and were trying to make some improvements in their app and took about a year to go live with us.
Once they finally went live, it took them less than 10 days on iOS to move from 2.8 stars to 4.7 stars. They were also able to move their Android rating from 2.54 stars to 4.3 stars. It did take them quite a bit longer, about seven months, to do that. The reason there’s such a difference in timeframe between the two platforms is that iOS allows you to actually reset your ratings and also allows you to have kind of a concept of current ratings. When they went live, it was before Android started rating newer ratings heavier. So basically, they were comparing current ratings to all-time ratings on the app. And they also…like I mentioned, while they were trying to implement Apptentive, they were trying to make some changes into their app. So, over that seven months, they continually were improving their app, were telling customers about what they did. So some of that was actually just organically trying to make customers happy. But that’s the kind of jump that we do very often see with our customers moving from, you know, two-something stars to over four and a half stars in a quick period of time.
So, if you are a company that does struggle with ratings and reviews, we have a few tips for you on how to improve ratings now. The first is, understand customer sentiment before prompting. If you’re looking to improve your ratings, you don’t just want to cast a wide net and let anybody, regardless of the experience they’ve had, go into the app store to rate. The reason for that is not just because they’re going to have more negative things to say. It’s because you want to address problems before you’re asking people to take a step that’s really more for you than it is for them. So, if they had a bad experience with you, you really need to remedy that situation. Give them the time to vent, fix the things that are wrong before you’re like, “Hey, could you go do this thing for me and rate?” So, it’s really important to understand customer sentiment before asking them to go and rate.
The second thing is you do want to respond to negative feedback. Whether you’re getting that through two-way messaging, through a survey, or even in the app store, you want to make sure that that information is not just going unnoticed, going untalked to. You want to make sure you’re closing the loop with those customers who have had a bad experience. So, they know you’re listening and they do engage with you even though they’re having a hard time. Robi was talking about moving customers from at-risk to fans. The way you’re going to do that is by closing that loop and addressing the problems that they’re saying, either one-to-one or at a larger scale if you have a large customer base.
And then the last thing is, from the data you’re getting, the raw feedback you’re getting either from ratings or reviews, from surveys, and then from messages you might be getting from customers, make sure that you have a way to analyze that data. If customers are telling you what’s going wrong or even what’s going right and what more they want to see, if you’re not taking the time to analyze that data, you don’t know how to build your roadmap to actually move customers along to a happier place. So, don’t look a gift horse in the mouth. Make sure that you are actually taking the time to look through particularly the raw data you’re getting from people because you’re going to find some things that maybe you miss in a survey that has close-ended answers that is going to help you to be a better partner to your customer.
All right. And now, I’m going to actually move on to our interactions and response rates. So, Apptentive has a number of different kinds of interactions. We’ve talked about the love dialogue. We’ve talked about surveys. We’ll get into some more information on surveys. But overall with our customers, we do see that they did talk to about 24 percent of their customer base throughout 2019. The focus here is not…it’s really similar to 2019 to 2018 and 2017. In general, we say that more interactions are better. So, our customers gave a voice to about 24 percent of their customer base. This is really good and is much higher than what you’d see from people not using Apptentive. But in general, giving a voice to more of your customer base is better.
Now, we definitely want you to focus on quality. We don’t just want you pushing surveys out to people not thinking about if they’re relevant to that customer base. We don’t want you just sending push notifications to people that have no relevance to what they’re doing. But, in general, the more you allow, not just feedback to go to or not just messages to go to customers, but a way for them to respond to you, the more they’re going to be engaged with your brand. So, we were very happy to keep that 24 percent but would like to see that move up in subsequent years. And then I want to talk about response rate. So, this is something we’re very, very proud of in Apptentive. For the fourth consistent year, we did see the response rates go up.
So, we saw a 94 percent response rate. That means for every hundred interactions our customers were putting out to their end consumers, 94 of them were actually responding back in some way, shape, or form. So again, more volume is great with interactions. But if we saw a higher volume of people, you know, being interacted with, but we saw a lower response rate, it would mean that our customers were annoying their end consumers. So, we’re really proud to see the highest response rate ever with one of the highest interaction rates, one of the highest percentage of interaction rates because it means our customers are talking to people at relevant times with relevant content and to the right people.
All right. And then we do have something called message center. You’ll hear us refer to that and it’s basically just a two-way messaging platform that allows companies to talk back and forth with end consumers. So, that is possible within Apptentetive. And what we saw in 2019 is a big jump in the number of inbound responses. So, the response is coming from end consumers into companies. And what that means is that we’re starting to understand how to use message center at scale. They understand the importance of giving their customers a voice with open-ended responses, open-ended feedback, and they’re learning how to close the communication loop at scale. So, just using message center, it’s really great if you have the opportunity, if you have a customer care team, to talk one-to-one with every single customer, but there are ways to effectively use message center by closing the loop at scale. Maybe it’s sending a note out to a group of customers to explain what you’ve improved, different things like that. Basically, customers are getting more comfortable on a large scale with getting open-ended feedback from their customer base and we’re really happy to see that.
All right. So I’m going to talk a little bit, give you some tips on how to engage more customers now. The first and the most important thing that you can do is proactively ask customers for their feedback. If you’re expecting to hide a survey or a Contact Us button somewhere in your hamburger menu on your app and you think that that’s how you’re going to engage with your customers, I can tell you, you have a silent majority of your customers that you’re not hearing from. They’re not going to seek that out. You need to proactively be asking them consistently over time how they’re feeling and also giving them information from you. Especially with everything that’s going on right now in the world, one of the only ways you have to talk to customers is through digital. And if you’re not building a gap between what you might have in a brick and mortar situation normally and what you wouldn’t normally do in your digital space, you are basically not talking to your customers at all. So, it’s really important that you do proactively ask for feedback from your customers, and also provide them with information so that they can continue to feel engaged with you.
And then the second thing is make sure that you’re working with a customer experience partner that enables you to reach out proactively. Make sure that you have something that either both can reach out to customers at scale and can allow you to respond back individually, and also make sure you’re working with a partner that allows you to measure sentiment over time. If you don’t know how your customers are feeling from one month to another, you don’t understand how to message them at that time and how to be relevant for them. So, make sure you are working with somebody who provides you that opportunity, not just as a one-point in time to a customer, but to ask the exact same person over time how they’re feeling. All right. And I’m going to hand things back over to Robi to talk a little bit about surveys.
Robi: Yeah. So, surveys, when we talk about customer feedback, people usually say, “Oh, surveys. You mean surveys.” And surveys are definitely a very important piece of the puzzle in communicating with customers. But as Christy was sharing, open-ended feedback messages, that’s a real opportunity for customers as well. But because surveys are so popular, we’ve taken a lot to heart around what’s good and what’s needed improvement around service. So, we’re talking about it through that lens. So in 2019, we saw 45 million surveys delivered. And across these 45 million surveys, we saw a steady response rate of about 18 percent. Now, 18 percent compares to the industry averages that we see in about 10 percent. So, it’s much higher, 80 percent higher. We feel pretty good about that, especially because we’ve increased the volume from 35 million to 45 million over the course of the year. And we saw similar response rates. So, we’re really proud of that.
Like Christy said, we don’t think you should annoy customers. We think when response rates decline, that’s really a sign that you might not be doing the right things. So, we’re proud of this, but we’ve also learned that there’s a way to get better. You don’t just have to put a certain thing in front of people. You can actually design an experience around it such that people know what’s coming up. So, if you’ve ever gone to a website and immediately upon entering that website, a pop-up intercept survey has said, “Hey, tell us about your experience. We’re asking these questions,” you kind of know why a lot of surveys don’t get answers, right? That’s not really the right time. What we have learned is setting an expectation using a note, actually linking interactions that take people on a journey, really increases response rates. Over half of end consumers when you tell them, “Hey, first, I would like your feedback, would you answer a survey about XYZ because you’re in this group,” over half of the people who choose to go through that interaction will answer that, right?
So, then what we’ve done is moved from a place where 18 percent feels pretty good to half, 50 percent, of people actually answered my survey. And so, we’ve driven a lot of customers into this path. And the fundamental truth is if you go on a path where you’ve got a much higher response rate, you’re annoying fewer people. So, that gives you and your teams more confidence to like we’re talking about, you know, beating this drum, talk to more customers. If you can do it in a way where half of the people are going to ask or answer the questions you’re asking, you can be pretty confident that people are ready, right? They’re really ready to share. So, this is really, really powerful.
And because of this, you’re able to get to a lot more customers. You’re able to get to a lot more of your overall spectrum of consumers to hear about what’s going on. And so, we know NPS is a topic of conversation, and a lot of orders around the industries, that a lot of CEOs, CMOs, CXOs are really saying, “We need to measure and test.” And we think NPS is useful. We think there are a bunch of reasons why NPS sort of is like, you know, 20-years-old and not necessarily designed for understanding customers over time. But we powered this, and what we’ve found is by increasing the number of customers you get to, you get a better sense of what NPS really is. People often say that a good NPS score, an average score, is 40 to 50, but what we found is our customers and other channels like email or phone surveys or intercept on the web are really getting 1,000, 2,000, sometimes if they’re lucky, 20,000 customers responding to these NPS surveys over the course of the year. And that’s what’s determining for a company that has millions of customers that they have an NPS of 40 to 50.
When you flip it around and you say, “Well, let’s get in front of more people, let’s link it to a Note. Let’s get 50 percent of people to answer this question,” the score drops, and that’s not bad news. It’s true news, right? It’s actually telling you what’s real for your customers. And blended it’s 25. That’s the average. Android NPS is by and large lower. We think that this tends to be because a lot of companies have invested behind iOS on the Android. We think that that seems to be the case, but there’s also a bunch of different issues around hardware and compatibility that we do, you know, a less seamless experience than they do on iOS.
Overall though, what we want you to understand is that when you talk to a lot more people, your NPS is going to come down, and you should set those expectations internally and flip around the conversation to, “But why is it okay to have a 45 NPS and only a thousand people are answering this?” Flip it to, “Well, what if a hundred thousand people answered this, and the real answer is 25? Well, we’ve got some problems and we can address them. Really, really important. This is what we’ve learned. The benchmark here is 25.
Now, talking about surveys and how to think about this, not just through the NPS lens, let’s tell you a story about a customer of ours that we’ve been working with for a number of years. Now, this customer’s really savvy, really digital, allowing people to pay with their apps in the early days. And like many of you that have sophisticated analytics packages, they were telling them what was happening, what people were clicking on, where they were spending time. And as a result of that, when they were doing re-design, they came to the conclusion that if you go through that, and there are a bunch of screens, one of the screens was just not used very often, and that was the menu screen.
They said, “Well, you know, a very small percentage of people are here. They’re not spending a lot of time. It’s probably not valuable. And in mobile, we’re always trying to really shrink your intention because it’s a small space. So, let’s take this out.” Almost immediately upon releasing a new version without the menu, the customer is swamped in the app store. They’re really, really unhappy. This vocal minority went and said, “Nope, one-star, fail. It doesn’t work. I can’t order it. I’m not going to go buy things.” And the reason, to them, was a little unclear. They’re like, really just taking away the menu. That’s all. Right around that time, they partnered with that tenant. They said, “Okay, we’ve got a problem. We need to figure out how to get in front of this.” And as soon as we were partnered and starting to collect feedback using some sophisticated surveys targeting customers who had said that they were unhappy and asking them why, the menu item issue popped up, and what they learned was something that only feedback can really tell you. Analytics don’t tell you.
The people who went to menu really needed the menu because they had either dietary restrictions or allergic reactions and if you didn’t have the menu, they didn’t have confidence to order. So, it made them unhappy, make them fearful, and it made them less likely to purchase. Really, really big problem. Analytics can’t tell you that. Feedback tells you that. Feedback tells you why. So, they iterated on product, released it again with the menu, and then went out in front of all a bunch of customers to say, “Hey, can we solve your problem? What’s going on?” And within two weeks of releasing the new product or really the old product with a menu, over 1,100 pieces of feedback came in from people who were like, “Thank you. Thank you for listening to me. I’m so grateful. This is really, really important.”
And it really changed the mindset inside of this company of, “Well, if we’re going to make some changes, why don’t talk to the customers who are using the menu feature before we get rid of it? If we’re going to make changes in a specific area of the app, why don’t we talk to the people who are using it? If we’re going to make changes to our loyalty program, why don’t we talk to our most loyal customers and our least loyal customers and understand what’s going on?” That real ability to focus and target proactively before making the change is a really powerful shift in strategy. And when we think about this, what this means for you is you can improve your surveys in a couple of really important ways. The first is thinking about the right mobile moment, right? Thinking about, “Here’s a customer using a survey or using a menu. I want to learn from them using a survey on why they use it.” That’s the right moment to understand that and use this So, that’s step one.
Thinking about who they are. Okay. I want to learn from people who are my loyalty members, why they’re not using their loyalty points in order to redeem it for free drinks. Being able to target based on those attributes. Like they’re in your loyalty program, they purchased something. They’re in this country. They’re in this region. They use this carrier. That’s really important to designing a survey that is going to have a high response rate because you’re learning just from the people who are appropriate. And then finally, connecting that qualitative data and the quantitative data. So, it’s not just what people are doing, “Oh, you’ve spent five minutes on the menu page, but why are you doing it? What do you use this for?” Being able to connect the dots on both of those things is really, really valuable. So, Christy, we’ve talked a lot about these interactions and the response rates. Let’s talk about this from a category perspective. Can you share some of the things we know there?
Christy: I sure can. Before I actually get into the category information, just an important reminder. I went over this a little bit ago. But the more customers you reach out to, the better the benchmark. So, make sure you’re able to track information by individual and you’re able to actually able to understand on an individual level how people are feeling, what their feedback is in different things. And again, make sure you are measuring the same people over time. So, let me get into the benchmark data. So, the first thing we’ll talk about is love percentage. Again, this is the percentage of people who said they love the app versus those who said that they didn’t. And the biggest takeaway here is the categories that you tend to see higher love percentage, those like finance, a lot of that is just due to the nature of the business.
So, in general, you’re going to have one bank that you use, and you’re not going to have a lot of options on that once you commit to that bank versus something like food or drink where you have many choices who are all competing with different innovations and different offerings. So, if you’re in one of the categories that has a lot of choices, you’re competing against everyone else in that category to keep up with the things that they’re offering. So, when mobile order and pay first started, the companies who actually introduced that first had a huge advantage with people loving their app. And that continues to this day. So, when you’re in a category that does compete a lot and it’s easy for people to transition from your company to another company and back again, you’re generally not going to see as high of love percentages. If you were in a category where people are more locked into what you’re doing, as long as you’re providing a good experience, it’s going to help raise the love percentage. And that’s really the biggest difference we’re seeing or why we’re seeing the biggest differences between categories with regards to love percentage.
And then we’ll talk about retention, which is a little bit the opposite of that. So, we do see some similar retention across the board for most app categories. The one exception to that is going to be shopping, and that’s when more customers do have the opportunity to switch very quickly and very easily between your product and someone else’s. It might be a different brand or something like that. But generally speaking, they’re able to get a shirt from a lot of different places. And we do see the retention tend to drop for shopping. One of the reasons for that, that we’re seeing it there and not as much in another category like food and beverage where there were a lot of choices, is because of the nature of shopping apps. So, companies in travel, in food and beverage have done a really good job of helping to blend the brick and mortar in-person experience with the in-app experience.
They make the two seamless and they make them feel part of one process. It’s been a little bit harder for companies in the shopping category to do this. So, generally speaking, you don’t need your mobile app in order to go shop in a store. You might use your mobile app when you are, you know, on the go or something like that. But you may also use your desktop apps. So, companies in that category haven’t really cracked the code yet in how to make the app relevant to the rest of the experience. And that’s why we see a drop-off in the shopping category in particular with regards to retention. And again, mostly across the board within a few percentage points, we do see a really similar retention amongst the other categories.
And then I will talk a little bit about express sentiment. So, in this realm, just because, as Robi mentioned, you’re seeing a shift here of a few percentage points, it doesn’t mean it’s not anything. So, just to highlight a few things here, the red that you’re seeing is the percentage that shifted from fans to at-risk. And the green are the ones that shifted from at-risk back to fans. So, it’s a small percentage, but if you think about this month over month if on average, let’s say in travel, 3 percent of people are moving from fans to at-risk, that’s 3 percent of your business every single month that could be leaving. If you’re in a category that has a higher average on shift, so, say you’re in finance, I mean, that’s a huge thing here. If customers are going from being a fan of yours to not being a fan of yours, yes, it is a bigger jump for them to leave and use another product. But once they’re gone, they are gone, and you’re going to lose that revenue from them.
So, think about the fact that if you were just to focus on that 3 percent, that 5 percent, that 6 percent every single month, if you could retain that extra percentage and keep them from going to a competitor, think about how much revenue that would mean over the course of a year for you. That’s the biggest thing we want to point out. There’s not a huge difference between categories, but if you are in one of the categories that has a higher shift, really do think about your strategy for shifting from or focusing on those who have shifted from fans into that at-risk category over time. All right.
Now, I’ll get into a little story now. This is from a very large global media brand who’s been an app kind of customer for a long time. And they have a few apps that actually turn on and off the love dialogue. This is not something we recommend, but it’s how they like to run things. We let our customers do what they want, but they’ll run it for a month or for a couple months, and then we’ll turn it off for a few months. And what we actually saw from them is, for instance, in the top app, the top brand in this media company, they were turning their love dialogue off between December and January and saw a 23 percent retention and then they turned it on again for half of January and February and saw the retention actually shoot up for that same length of period to 29 percent. And similarly, in their other app, they had love dialogue running for the first half of January and then turned it off for the second half and saw a 7 percent drop in retention for that time period. So, Robi and I have been saying this throughout this webinar, but it’s really important that you do talk to your customers, that you do ask them how they’re doing over time. If you’re not taking the time to engage with them and to make them feel like you are a human on the other end who cares about them, you are going to lose them to a competitor. And this company did see that kind of the hard way and understands the value of having that continual conversation over time with customers.
All right. So, I’ll talk just a little bit about ratings within app categories. The main thing to think about here is when you’re looking across the board, the thing that stands out is media companies tend to have a higher percentage of one-star ratings. And a lot of that is not just because people are going in and giving feedback on the app. It’s not like their apps are really terrible. When people go and leave feedback in the app store or in Google Play, a lot of times they’re getting feedback not just on your app or not just their experience, but on the brands and how they’re feeling. Media tends to be a really polarizing subject, particularly in this day and age. So, we do see people that are going in and actually just giving negative feedback because they don’t like the brand in general. They don’t like their political view. They don’t like their anchors, whatever it is. We tend to see a higher percentage there.
And what you can learn from that is, if you’re a company who is experiencing issues with the number of one-star ratings, it’s really important, again, that you actually get in front of your fans and ask them to go in and rate the app. Ask them to go and spend that time because what’s going to happen is you’re going to see that shift. When you have a silent majority and you’re just letting people who want to be really vocal and who want to express their opinion go in and you’re not asking the people who would not be apt to do that on their own, you’re going to see ratings go down.
If you’re actually taking the time to ask your customers to go and do something for you, to take a quick second to leave their rating, you’re going to see that percentage of five-star ratings go up, and it therefore consequently is going to make that silent majority who is just super, or sorry, the vocal minority who’s just super angry with the content, with one particular thing you’ve changed in your app, you’re actually going to make it so that they’re just a smaller percentage of the people leaving ratings. And then talking about reviews, so you’ll see a pretty big difference here between different categories. And ultimately, the thing for you to remember, this is important for you in your particular app categories, but looking between app categories, the major difference is usage of the app. So, companies like food and drink because again, you have a lot of people using them.
There are a lot of people that you can actually ask for ratings. You’re going to see a higher number of reviews in those categories. You only have one bank, but you have a lot of places that you can choose to eat. There’s a lot more potential to ask people over time for those reviews. And then lastly, for this, I’ll talk about interaction rates and then I’ll get into a little story. We are seeing a difference between app categories and interaction rates. So, some categories like food and drink really have a lower percentage of interaction rates and that’s because they have limited opportunities to show customers interactions. So, they do have a higher percentage of people going and leaving reviews. But, because the apps are so much more transactional, it’s hard to get a right place and time. If you’re on the app for one to three minutes just to put an order in, the companies don’t want to necessarily be super noisy.
So, it’s harder to choose the right place and time to actually speak to your customers with meaningful content over time. If you have something more like a finance or lifestyle app or a media app where you’d spend more time in the app per session, it’s a lot easier to find that right place and time to find a break in what the customer is doing to serve them in interaction. So, a lot of what we’re seeing is due to the nature of the business. We are working very hard with customers in things like food and drink to understand that they still do need to give a voice to their customers even if it is a little bit more difficult. So, it’s really important to have a strategy around your communication and to plan ahead for what that communication is going to look like over time, so you can consistently be giving your customers a voice.
On the other end, we are seeing huge, huge numbers in things like lifestyle. And I’ll get into a story about one those lifestyle companies and why we’re seeing such high interaction percentage. So this particular company, again, it’s a global telco company. They do a really good job of engaging their customers. Their customers really, really love them and are very loyal to them. And because of that, they actually have a partner app that allows you not just to see usage of telco and things, but to actually, you know, get some offers and things like that. And this particular company goes in every Tuesday and runs a six-question survey around the deals that they’re offering and around how they found out about those deals. And what they found is that every single week, they’re able to collect about 2,000 responses in 15 or 20 minutes.
So they just ask their customers, “What did you think of this? How did you find out about it? Is this the type of thing you’d like to see in the future?” And they see it varies per week, but it’s between 15 percent and 60 percent response rates, and they get their target number of responses in just 10 to 15 minutes a week. And with that, they’re able to measure over time sentiment of how customers are feeling about the offers. And if you’re on the right track, so you use your obviously customers that are super loyal to them, they want to be super loyal to those customers and provide them with some perks. So, it’s really important that they get the right parts to the right people. So, they are talking to a large percentage of their customers. That’s something that’s driving up that lifestyle category from the page before because they are actively going in every week and just gauging their customers to make sure that they’re doing the right thing by them and they’re bringing them back every week with the right offers.
All right. And the last thing I’m going to talk about is Apple responses. And this is responses by category. You will see that there is a pretty big difference. So, lifestyle, for instance, it has about a 2 percent response rate, whereas some of the higher ones are seeing more like 98 percent, 97 percent. The thing to notice here is some of this has to do with the kind of interaction you’re displaying. So, if you’re displaying something like a survey, you may have a lower percentage of completion rate than something like a note where they just have to click a simple button to respond to you. So, some of this has to do with the type of interaction they’re presenting. But the thing I really want to point out here is the low point of customer interaction is about 82 percent or of response rate is about 82 percent.
So, for every single interaction they’re putting out, they’re getting an 82 percent response rate. If you were looking at this and saying, “Wow, our response rate is 20 percent,” really consider if you have the right strategy and if you have the right CX partner to get you the kind of response rates that you’re looking for. You need to be considering right place, right time, and right audience, have a complex targeting tool where you can actually talk to the right people. So, if you’re looking at this and your response rates overall are not that high, we’d love to talk to you. If you’re a customer of ours and you’re at the lower end of this, we’d love to talk to you about optimizing how to get that higher. So, that is it for my slides and I will pass it back to Robi.
Robi: Awesome. Thanks. Thanks, Christy. And I know this is a lot, right? So, what we have for you are some followup steps, right? We’ve got an industry-focused section of the report that you can click on to get more detailed just about your industry and to be able to compare your app’s performance. So, as mentioned at the beginning, this is gonna be shared afterwards in the follow-up, but then these actual tips, the thing that we’re talking about the most is you can hear from more customers. If you’re not hearing from a quarter of your customers… I think this is the biggest headline. If you’re not hearing from a quarter of your customers right now, when you’re trying to figure out what the future looks like, when customers are gonna come back to your stores, what their shopping behaviors are going to look like, you can do it.
If you’re below 25 percent, you can move up to that range. That’s the average. You could potentially get to 30 percent or 40 percent. And when you do that, you can increase retention because you’re going to be able to predict churn. You’re going to know when customers are unhappy before they leave if you’re talking to more of your customers. That’s what you can do right now. We got a couple of questions that have come in. We’re going to stay here until the questions are answered. I’m going to just take a couple of these right off the top. If you have not hit the Q&A button and you’ve got a question, please do that and then we’ll see this more through. But the first question, right, for those people that shift from risk to fan, Christy, what tactics have brands taken to achieve that result? So, getting a customer to change their sentiment and changing from risk to fan, what have they done? How dos customization and personalization impact that?
Christy: That is a really good question. One of the things to think about is this is going to be really individual to specific customers. So, at Appentative, the customer success team is really focused on engaging with an individual customer on their needs versus overall. So, it really does boil down to just you need to make sure you’re actually talking to customers and you’re closing the loop. So, if you’re putting out a new feature, if you are, you know, improving something in the app, if you have an outage coming, all of those types of things, it’s really important that you’re talking to customers and letting them know that that’s happening or that that’s going to happen. But, as far as specifics on that, it just depends on what your goal is as a customer. So, if you are a customer, and I’m not sure who this question came from, but if you are a customer and this is something you’re struggling with, please reach out to your customer success manager. We’d love to help tailor a specific plan to you.
But, in general, just make sure you’re closing the loop with people and actually letting them know what’s going on. The more they’re hear…if they’re not hearing from you at all, just assume that they think you don’t care about them. Think about if you were to go into a retail store and no one greeted you. You wouldn’t feel wanted in that store. You wouldn’t feel like that’s something, you know, where that team cared about you or if right away they asked you if you wanted a fitting room before you had actually taken the time to put anything on your arm and, you know, get any garments, that would not be a good experience for you. So, when you’re considering what that communication loop looks like, consider what points you’d actually need to tell customers things throughout their journey so that they know they’re being heard and they know you understand their experience.
Robi: Awesome. And we’re right at 11:00 a.m., so I know some of you hear me dropping off again. We’re going to follow up with this, the recording. We’ve got another question here that’s sort of bread and butter for me. I love this question because talking about, to me, is terribly interesting, which is why isn’t NPS good enough? We talked about NPS. We talked about how people are measuring it, and I get why maybe the numbers should be lower, but you said it’s also not good enough. Why not? And here’s the challenge with NPS. As it was conceived many, many years ago in like 2001, it was conceived as a measure to help companies assess growth. But what it has turned into is in a lot of companies it has turned into a measurement that people are bonused against, that incentives are aligned around, and as a result, a lot of teams fundamentally game NPS. They look at it as a measure that they have to move up and up and up.
It’s not necessarily a listening measurement that allows them to learn about where to go. And so, even that vein, right, NPS is really, it’s not hitting its potential. What it was designed for is predict growth, if you’re hearing for a lot of people. When you’re hearing from 1,000, 1,200, 1,500 customers, you’re just really not doing what’s necessary in order to take your business forward. The other thing about NPS that really is a struggle, there’s a lot of people execute NPS to channels that are very different. So, if you’re collecting most of your NPS through email, that channel by being email actually ages, right? It tends to have an older segment of your customers answering it, looking at the emails, clicking through, and answering it. So, when you’re trying to understand your overall NPS as a company, but then you’re mostly delivering it through the channel of email, you’re skewing the results of the people who read email are actually clicked through and then respond. So, that’s another problem with NPS.
And then the third problem with NPS, and it wasn’t really designed this way, people definitely don’t use it, is it doesn’t help you understand how a specific customer has changed in their answer to that question. So, you can take a measuring Q1 and say, “Our NPS is 46 and measuring Q2,” and say, “All right. Our measure is 47,” but it’s not the same set of customers. And so, what you’ve learned is just for a different group of customers who are about the same, but you don’t know if that customer who gave you a nine on that yes score three months ago is still a nine or if they’re at a six. And when you’re not tracking that over time and yes, NPS really not relevant to you. You’re not understanding if you’ve done anything to shift it. You’re just measuring from a thousand people to try and get a score. So, that’s a challenge.
All right. Let’s see. I’ve got one more open question. Okay. This is not a question, but it is, “I like the cat picture in the background.” Yes. My wife painted this at a Bob Ross party actually at one of our CSMs, Pat Cotter’s house years ago in 10 minutes. So, fantastic. All right. With that, I think we’re at time and at the end of the questions and comments. Thank you for joining us. Really, really a lot here to discuss. We shared a lot of data. Please follow up with this if you have questions, if there’s ways that we can be helpful. Talk to more of your customers and listen to them. Cheers.
Christy: Thanks. everybody. Have a good day.