Preact

Before starting Preact, I consulted for a large web company on a project where I built wireframes and created concept visual designs for a new product they were going to be releasing. One of my favorite parts about that job was the fact that I wasn’t limited by specs and requirements, and that I had the freedom to let my imagination run wild. I could ask myself the question, “What kind of information would I find useful to complete X if I were on this page?” I remember putting the development teams through their paces as they scrambled to find out if they were technically able to pull some of the associated data that I wanted to use and display.

The thing that really drove me back then was the ability to take a simple concept and bring a new perspective to it - one that wasn’t limited by constraints or technical limitations. Instead, I had the opportunity to ask, “Wouldn’t it be cool/useful/awesome if we could ______?”, and then explore that possibility.

Ever since starting Preact, this has been one of the main focuses of my job. And it’s really what our customers are looking for when deciding on a customer success platform. The underlying question is, “Can I use this customer success platform to make a difference in my bottom line and in how I communicate with and understand my customers?”

Anyone can collect customer data and regurgitate it to you; that part is easy. The thing we focus on at Preact is answering the question, “What does this mean, how can we present this information that makes sense, and how can we make it actionable to the type of person looking at this data?” We have the unique challenge of creating actionable insights for C-levels, account manager, sales teams, support and success representatives, and product teams - all in the same product. As a result, the challenge is much larger. But that’s what makes it exciting.

As an example, I thought I’d show some of the work that led up to our most recent version of Preact Sidebar, our portal to presenting customer activity.

In a very early version, we focused very heavily on visual events. And of course, customer activity timelines look great when they're full of pictures, but you have to make it work when it's full of other types of data.

Another iteration showed summaries of types of events. Maybe interesting. But useful? Not really.

Or what if we tried to come to conclusions about users that would help our customers make more informed decisions? The mockup below, for example, pointed out why this user was important and highlight trends that made them differ from the average user. This information can come in handy when communicating with them. (Are they a novice or a computer wiz?)

We condensed into more of a sidebar timeline and came up with something like this, trying to only highlight events that are relevant to you as a user.

If you were an account manager, you might see this screen that included some high-level stats.

Or we could throw a bunch of unique charts and graphs on the page.

Or what if we broke things down into sessions and highlighted important events in sessions?

Or maybe we can find a happy medium between charts, insights, and stats.

None of these are what we have in production today, and are miles behind what we are working on now. But I hope this gives a little insight into how we build product. And when you're creating something no one has ever built before, the challenge is that much greater. There are no competitors to copy, and no ideas to steal.

Preact has the very unique opportunity to make sense of loads of customer data. If we simply regurgitate collected data onto a page, there's nothing exciting about what we do. But when we start asking questions like, "What does this data mean?", "How does their activity correlate with other events?", and "What kinds of patterns can we discover that make a significant impact in the long-term value of this customer?", then we can start to find and present relevant insights that our customers have come to rely on us for today. And we're just getting started.

There are many moving pieces in a successful Customer Success organization. Customer Success falls into every department of the company. 

If Customer Success falls in every department then what are Customer Success Manager's responsible for? Onboarding, Training, and Consulting are all responsibilities of the CSM team and are all extremely important. It is similar to a Teacher - Student relationship. The CSM is the Teacher of product and the customer is the student. It is the CSM's job to make sure their customers learn the best practices about the product and industry (if necessary). 

Below are common questions and challenges that CSM's face

1) Does my customer know best practices for our industry that allow for a better experience with our product? For example, if you sell an email automation tool, does the customer have basic knowledge of email marketing?

2) How do I make sure that my point of contact is working towards a full integration with my product, and not just half way? If they only implement / learn  ⅓  or ½ then they are not getting the full value. Or even worse, not using key features that make the product great.

3) If they can’t remember where their at in the integration phase or what they have or have not done, how am I suppose to provide the right guidance?

4) How do I get them excited and motivated to finish integration and learning about our product?

One small change you can make is to have a  Getting Started Introduction Meeting. This is a video call where you walk them through the product more in depth, set up the integrations (eg. salesforce - using a screen share to guide them), assign tasks for them to do before your next video chat, and get an idea of their knowledge base. Essentially you are setting up a series of training sessions that is specialized for each customer.

It is also a good idea to track their Onboarding. What are 4-8 key actions you want your customers to take right when they log into / start using your product?  At Preact, we use our Onboard Tracking Feature which is presented in the form of a checklist in the Preact Sidebar. These are key steps within our product that we feel are crucial for the customer to do at the beginning. For example, we want to make sure they have 1) taken a tour of the product 2) downloaded the chrome extension 3) viewed a report ect…. The Preact Onboarding Tab helps our CSM team get a better idea on how to specifically help their customers on a individual level at the right time and check their progress. 

It’s day 2 of 2014. Most of us spent yesterday looking back on 2013, making resolutions for 2014 and fighting a massive hangover. What were you thankful for? What changes are you going to make? And what do you predict for 2014?

At Preact, we can look back at 2013 and see all the progress we’ve made with the product, sales, and team. Our resolutions are to raise the bar, work even harder than we have this past year and continue to create an amazing product for our customers. We predict that Preact will dominate and transform an emerging market. This market being Customer Success.

Yes, there are other companies in this space. (if anything, they are validating the market along with Preact, which is never bad!)  However, in 2014 Preact will re-define what Customer Success currently looks like, more specifically, the way SaaS companies calculate and predict churn. It’s our secret sauce, it’s our team of data scientist, it’s the way we use cyclical metrics and adaptive models for account health, it’s our quick on-boarding process, it’s our supporters, our hard work, and great customers that are constantly improving Preact.

Two facts about starting a business in 2013 and 2014...

You can start your own business more easily

You will have more competitors

Catch 22 right? So how do you differentiate?

9 out of 10 US consumers say they would pay more to ensure a superior customer service experience

86% of consumers quit doing business with a company because of a bad customer experience 

Statistics like these (and many more) coupled with emergence of the social graph, have taught us that customer service is THE deciding factor when picking one product/service over another, so much that they are even willing to pay more for it.  

It’s the end of 2013. You and your competitors have jumped on board. You are all spending money and time (as you should be) on livechat software such as zendesk, helpscout, desk.com ect... in order to differentiate yourself in the market and “create a better experience.” Wait, is this another catch 22? I am doing this to differentiate but everyone is doing it too? That’s not differentiation. Ding Ding Ding! You’re right.

Customer support is no longer a differentiating factor, it’s now the standard.  You’re answering all your support tickets. But so are your competitors.

Now what? Great customer service is no longer driving more business to you and doesn’t make you stand out. And if you are unlucky, you were late to join the bandwagon. You just started (or are starting to) implement a good customer service experience.

So what’s going to be YOUR next competitive advantage? Where is support moving? And how can it save you money?

The next step in support is knowing what your customer’s are going to ask (or not ask) before they say a word to you.

For every customer who complains, 26 other customers remain silent.

For example, your customer, John Doe, hits an error on your site. He was unable to successfully upload a photo. Before he sends you a support ticket, you have already reached out. You let him know that he was unable to upload his photo because it was in a tif file rather than a jpeg file.

Everybody is in the win win here:

You win...  

cut down support ticket time (aka save $!)

impressed a customer

differentiated yourself from competitors

John Doe wins...

problem was solved asap

he put little to no effort into solving the problem

feels valued as a customer

Great news: it seems that more companies than ever are putting a greater focus on customer success. Perhaps these companies have noticed the great success of customer-centric companies such as Amazon, Zappos, and Salesforce. Perhaps they have read the statistic that it costs 6-7x more to acquire a new customer than to retain an existing customer. Whatever the reason, one thing is certain: this trend is positive for the companies experiencing more loyalty and the customers receiving a better experience. However, not all customer success tools are created equal!

  Since it is the holiday season, I feel it’s only appropriate to illustrate this point with a holiday example. Imagine you are going to buy presents for your 8-year-old son, your significant other and your mother. Would you buy all of them the same exact thing?

  If you answered yes, I would be very intrigued to meet your family. For the 99.99% of you who answered no, why? The simple answer is that they are different people with their own interests and personalities. The football you buy your 8-year-old son probably isn’t the best option for your mother. The romantic trip you give you significant other would be pretty odd to give your mother. The “World’s Best Grandma” shirt you get your mother would be poorly received by your wife.

  The one-size fits all approach doesn’t work for holiday gifts. It also doesn’t work for customer success tools. Why? Because all of your customers use your product differently. Some of your customers use your tool everyday while others use it once a month.  Your enterprise customers use your service differently than a 5 person small business. Most customer success tools are approaching the problem with this Static Approach. They ask you to define churn and engagement across your entire customer base, and then they simply tell you who is and is not meeting those criteria.

  At Preact, we think a better way to approach customer success is to treat every customer as a unique individual who uses your product in his or her own way. Enter the Science Approach to customer success. Using data science and machine learning, Preact learns how each individual uses your application and automatically creates a unique profile based on how often they login and what they do during a typical session. This means you will no longer be trying to save an account after 2 weeks of inactivity when in reality they only log in once a month. Similarly, you will be alerted of customers who are at danger of churning even if they have not reached the arbitrary number of days of inactivity that the static approach requires.

We've been in our new office, aka "The Sunroom", for four days now. These have been our observations/experiences thus far:

Despite it's name, The Sunroom is not, in fact, warm or sunny. It's freezing. Cory and I are displeased, while Gooley seems to be thriving in the frigid temperatures. 

We have discovered a worthwhile contender for the Taco Tuesday tradition: The Iron Cactus.

I have become victim to the "commuter sneaker". Yes, that's right; I have special commuter shoes. I feel like this is more acceptable in San Francisco than LA, as the closest BART station is a mile away.*

We are slowly, but surely, making friends with the other people in our co-working space. Scratch that--just accidentally cut someone in line for the coffee machine this morning. But, it is really nice to be around other humans.

Gooley just signed us up for EAT Club, which is basically the most awesome perk ever. Their 'get started' email just says: "Sign up and order your lunch by 10:30AM. Your lunch arrives no later than 12:30PM". No thrills, no frills, just tell it like it is. That's my kind of lunch.

You know what, San Francisco? You're OK. I think we'll stay.

A large part of determining account or customer health is building adaptive models of what "normal" behavior looks like and then reacting to behaviors that deviate from these models. In many cases the question can be put simply: "How often does a healthy account or customer engage with feature X?" and "How healthy is an account or customer given their engagement level with feature X?"

One common case is when an account or customer pays for a monthly subscription to a product or service. We might expect a healthy customer to come back each month and engage with the product or service at a level that meets or exceeds their previous engagement. But how can we know when a customer starts to fall below their typical engagement level? Is there a way to be certain (in a statistical sense) that what you are looking at is abnormal?

Our approach to solving this problem is to build a model for each account or customer for signals that are anticipated to repeat themselves month to month (i.e. engagement levels, counts of actions performed, etc). The model adapts to the historical trend and tells you for every hour in the month what you should expect to see and with how much statistical confidence.

The image above is one such model. The red circles are the recorded values for a certain customer action count (i.e. sending emails) and the blue line is what we predict to happen based on this history. The model provides not only a prediction but a confidence interval for each point in time and plotted is the 95% confidence interval.

A simpler approach would be to make predictions from a linear model. The linear model is built on the following logic: we know that by the end of the month 200 actions are usually performed, if it's 50% of the way through the month we expect that 100 actions will have been performed by now, etc. This is the model reflected by the red diagonal dotted line. As you can see, the linear model neglects a large amount of predictive power of this signal. Namely, we can see from the plot that this customer tends to over-engage at the start of the month and taper off toward the end. This is captured by the more flexible statistical model that we created.

The flexible statistical model we developed is capable of fitting a wide array of behavior patterns and adapts automatically when these trends change. In the image above, you can see how the model accounts for the deviation in customer behavior in the middle of the month and as the newest historical data runs out (the red dots in the upper right) the prediction smoothly converges with the historical trend.

OK, great. You are a salesman for XYZ SaaS Company, and you just sold a customer your premium package. Your boss gives you a nice Commission check so you go home and treat yourself to a nice fancy dinner. The deal is done, the money is collected, and you return to work the next day in search for the next big sale. The previous customer is lost in a list of subscribers as you wait until their contract ends and hope to close them on a new one. The time between “contract signed” and “contract expired” is quickly transforming from a period of satisfaction to a span of opportunity.

“What do you mean by opportunity, the deal is done?”, somebody might ask. Recent studies have shown that it can be 6-7 times more expensive to find a new customer than to up-sell a current one. By no means am I saying that you should stop looking for new accounts, but more company time and resources should be allocated in attempt to increase recurring revenue through current ones. Whether it be a mobile gaming company with in-app purchases, a package upgrade of any SaaS subscription, etc..., there is always the opportunity to boost revenue through constant customer engagement and interaction.

You will soon come to realize, however, that the process of keeping a customer happy is a battle that is not easily won. Success agents are constantly walking a fine line between constructive and possibly destructive communication. You want to let each user know that they are valued as an individual, while simultaneously keeping your distance. Now the easiest way to enhance a relationship with a customer is to be available and quick to resolve any issues that may arise. But how do you stay engaged with a customer who does not send in a single support ticket? Do you assume that they are fully content with your service and seek no additional assistance? As a matter of fact, support teams are not aware of most issues because their users don’t take the time to report them. Here is where the opportunity is born! You simply need the right tools to capitalize on that opportunity.

Now you can also see the number of sessions and total minutes active per typical user of your app. Like all the other metrics on the dashboard, these are also based on the period you're looking at so depending on your site's user behavior you'll probably see one of two common trends.

Did you know Preact has awesome Stripe integration?

We've also enhanced the pie chart display for each event type so you can quickly see how usage is changing. When the portion of your audience using that feature decreases, you'll see a red pie chart section showing you the previous value and the black indicating where it is now.

When the active user percentage grows, you'll see a green pie section showing you how much it's grown from the previous period. For example, usage for the feature shown below went from less than 25% of users last week to over half of our active users this week. Guess that means the word is spreading, or you're doing a better job with interfaces that expose the feature.

If you're monitoring multi-seat accounts on Preact, you'll be excited to see how the new dashboard works for helping you understand the difference between individual user behavior and account-level usage. We've automatically added another column that shows the account metrics for each event on your dashboard.

If you're using Gmail or Google Apps to communicate with your customers, make sure you have the Preact Sidebar installed. We've just released a bunch of improvements to the sidebar, including making it play nicely with the Rapportive extension so that now the Preact Sidebar will show the same user that Rapportive is displaying.

You've probably been noticing changes to the weekly email you get every Monday. We have been updating it to be more relevant to highlight how your user's behavior is changing. For instance, now you will see these small sections for each of your key metrics, so let me explain each of the components.

If your account executives or sales team are using Salesforce, you are going to love the Preact Salesforce integration. In addition to pushing our proprietary analysis into your salesforce database (so that you can build custom reports and dashboards), we've also created new Apex pages so that you can view up-to-the-second information on all of your Accounts and Contacts.

We've been beta testing this integration with a couple heavy Salesforce.com users and are ready to start rolling it out to more people. Get in touch with us if your company wants to give it a try.

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