What does it take to create a case for customer education? Even if you’re a novice, how do you get started on the right foot? Listen to The Talented Learning Show!
WELCOME TO EPISODE 32 OF THE TALENTED LEARNING SHOW
To find out more about this podcast series or to see the full collection of episodes visit The Talented Learning Show main page.
EPISODE 32 – TOPIC SUMMARY AND GUEST:
If you’re a fan of Talented Learning, you know I’m obsessed with customer education. It’s not just because it’s the hottest segment of the extended enterprise learning market, but because it’s a fascinating specialty that blends marketing, instructional design and business strategy.
Bill is one of the few people in the world who truly has a finger on the pulse of customer education. With more than 160 episodes of his own podcast, Helping Sells, he is one of the best-known experts in this field. And today, Bill and I examine what it takes to develop a successful customer education business case.
- Customer training is unique – not just because it targets external audiences who participate at their discretion – but also because its business impact is relatively easy to measure.
- When building a case for customer training, it’s important to recognize that data is never perfect or complete. The best models are based on assumptions that are continuously tested and adjusted over time.
- The process of developing a customer education business case may seem intimidating or tedious. But it’s well worth the effort, because this is the most effective way to boost leadership confidence in your team, your mission and your methods.
Before we dig into today’s topic, could you tell us how you got involved with customer education?
My career started at eTrade, where I talked with customers about how to manage their stocks. This was in the late ’90s boom times and they were expanding rapidly. One day, they asked if one of us would teach new hires a class in investment basics. I volunteered to do it and I’ve been involved with training ever since.
What led you to customer education, specifically?
I focused on employee L&D for the first 10-12 years. But eventually, I lost interest in being considered business “overhead.” I also wanted to be closer to customers, so I started moving toward customer-facing training, where people pay to learn.
That’s where the action is…
Yeah. For example, I worked on elearning projects for customers at Accenture. Also, I was Chief Learning Officer at The Knowland Group, a hotel software company, where I developed customer training. Eventually, I joined ServiceRocket in 2013, where I focus on helping software companies improve and sell their customer training.
So now, I don’t have to worry about Kirkpatrick’s 4 levels of employee training evaluation. Instead, I evaluate training with invoices. That’s it.
Yep. My life is simple.
As one of the world’s few customer education experts, how would you describe the state of the industry? Is growth still accelerating? What do you see ahead?
I specialize in the software industry, so that’s what I know best. And in this industry, open source companies are the customer education leaders, in my opinion. There are several reasons why:
• When software is free, you have to make money with services. And training is a service. At open source companies, a customer training person is often an early hire and customer education becomes one of their first sources of revenue.
• Open source companies typically develop highly innovative technologies. In that situation, customer training doubles as marketing. They hire a fancy developer as an evangelist who also teaches the class. Fanboys sign-up to learn from these rockstars, then they walk away with your t-shirts and spread the word about your brand.
In other words, to build market momentum, open source companies lead with training. For customer success, they need product adoption and that’s a direct result of education.
Are there enough open source software companies to influence the direction of customer education, overall?
If you search Crunchbase for enterprise SaaS and cloud software vendors – and maybe even on-premise – you might find 5000 total companies in the world. Open source vendors are only a subset of that niche, with maybe hundreds of companies.
I’m generalizing, but many SaaS companies tend to treat training like an afterthought because they want to be scalable from the beginning. For example, they don’t even have enterprise sales teams. They want everything to be self-service.
Think of Dropbox. A company like that is certainly not likely to hire a training team and pay money for a learning management system. Instead, they’ll just post some help files online, produce some videos and that’s all they do to “train” customers. Because their business model is self-service. Right?
At least until General Motors wants an enterprise-wide license. GM will say, “When are you going to send someone to train us?” And vendor team members will look at one another and say, “Us? Are you crazy?”
So generally, there are two camps. One camp includes open source software companies like MongoDB, which may lead with training because it’s a service they can monetize. And if it’s 2009, who knows what MongoDB is? So they have to educate the market.
Meanwhile in the other camp, you have SaaS companies that want to lead with training – if they offer it. But training is going to be free because it’s part of the service. After all, service is the second “s” in SaaS.
Eventually, these two worlds meet in the middle.
One reason why customer education is so attractive is that it is highly measurable. You can quantify progress. What do you think are the most important customer education metrics?
It helps to map metrics to stages in the training management process. Here are three key metrics:
When you launch a training course, you need to know who intends to show up. So you track registrations or sign-ups or completions. Any of those will work.
Of course, if your strategy is video-first, and you deliver through YouTube and embedded online clips, you don’t really know who’s consuming your content. You just see clicks.
But if you build-in some kind of registration capability, you can start seeing who signs up and who shows up.
2) Contacts Created
You’ll also want to know when new people are signing up for training. Of course, this doesn’t apply if you gate all your training content and give access only your active customers. I think that’s usually a mistake, by the way. But you need to know when new people are signing up.
Did someone buy the course you’re offering? Of course, if you don’t actually sell training, you won’t need to track transaction volume or value. But otherwise, this is critical.
I would ignore all of the Hotjar heatmaps, and click-through data and drill-down analysis about “How long did someone spend on slide 17 of a 19-slide video?”
That’s important when you’re optimizing a mature customer training program. But at the outset, keep it simple.
Are people signing up? Are they participating in training? And are they paying for it?
Agree. That will get you out-of-the-gate. What about the next stage? What if people want to know which new contacts lead to renewals or incremental sales or complementary sales?
Yeah, those are phase two metrics, where you want tie training to an outcome, and you have to define that outcome precisely. Are they renewing more? Are they upgrading more? Are they buying more product?
Frankly, I think very few software companies are actually doing this. And if someone could solve this problem – which we’re working on – it would be a big deal for the customer education market.
Think of it this way. We help customer training professionals measure and analyze their program impact in a simple manual way, so they know how to do it themselves.
That’s because working with databases and data scientists and business intelligence analysts is difficult and expensive. Plus, customer education teams usually have to wait in line for access to data experts, because software companies have other priorities.
Would you briefly walk through this DIY approach?
Sure. You’re’ going to create several lists, so you’ll need a spreadsheet or even just a pencil and paper.
1) Make a list of customers that took training over a specific period of time. It can be last month, last quarter or last year. Just pick a timeframe that works for you. Let’s say you’ve trained 50 customers in the last 6 months. Enter this list on a spreadsheet in column A.
2) Make a list of customers that did not take training during the same timeframe. Enter them in column C on your spreadsheet.
3) Now for columns B and D, pick the outcome you want. Maybe you want to focus on opportunity size or deal size for each customer account.
You can find this in a CRM like Salesforce. This number is indisputable. Even if it changes, you know the value was $50,000 for X users of whatever software application they bought. So find the corresponding deal size for each account and enter those numbers in columns B and D.
4) Now you can calculate the average deal size for both columns of customers. Let’s say that among customers who took training, the average deal size is $10,000, but it’s only $5000 for those who didn’t take training.
Maybe a statistician would laugh and tell us that’s not very scientific. But you have to start somewhere and anyone can do this exercise.
So if you see a difference in average deal size, you need to decide if it’s a good difference. That’s a judgment call.
But you could take your spreadsheet to a data analyst and ask for a more informed interpretation. Chances are, the data scientist will offer more guidance. It may be, “There’s a better way to do this – let me help you.” That’s progress.
At least you can start looking for a difference on your own. If you don’t see it, a difference may not be there.
Or perhaps it’s there, but your data just doesn’t show it. That’s possible. Or you might wonder if the training, itself, is effective. Or maybe the customers who took the training were already good at whatever skill the training was designed to teach.
Now you’ve generated all kinds of reasons to do further analysis, right?
Also, you’re not limited to columns B and D. You can look at other account characteristics like days sales outstanding or the number of opportunities. You can even combine multiple factors to see where training makes more impact.
Totally right. But here’s a mistake people make with analytics like this. Often they want to tie training to an outcome, but they aren’t precise enough about how they define that outcome.
So they may want to include 10 different columns, each with a different metric. The numbers themselves may or may not be accurate. But the metrics they choose should be clear and specific. Because precision matters.
So let’s say a quick analysis reveals that deal size is 5x larger for trained customers who also have obtained certification. Excellent! But when you tell senior management, they say, “Put it in a business case.” Building a customer education business case scares many training professionals…
Yeah, customers ask us all the time, “Can you help me do that?”
OK, let’s run with your example. We see that trained customers have 5x higher deal size, so we immediately conclude that we should do more training. How do you develop the business case?
First, state your hypothesis. It should be a question. For example, “If more customers take training, will average deal size increase?” You start with a premise like this because you have some data to support it.
Next, establish a related goal. Again, precision matters. Obviously, the goal here is to increase customer deal size. But it could be different. For example, it could be getting more customers to take training, because that could lead to having more customers with a higher deal size. It doesn’t really matter which concept you prefer, as long as it’s precise.
So let’s say your goal for 2020 is to double the number of 2019 customers who completed training. And in this case, a customer is an account. So that’s a total of 50 x 2 = 100 additional accounts. Or you may want to focus on increasing training among individual users within accounts, because that can make a bigger impact on your business.
The next part of your business case should be that ROI-investment-payback thing. So you say, “If we get those extra 2x accounts to take training, we think the average increase in deal size will be $10,000. So 100 accounts x $10,000 = $1 million total increase.
Or say you want to increase aveage deal size from $5000 to $7000. So now you have an increase in dollar amount going through the system. That’s your hypothesis, and hopefully you can beat it. But that’s your plan. Your goal is to move the “return” part of the ROI calculation – to increase deal size by $2000 on average.
Okay. For this $2000 increase in average deal size, what next?
Do the math. Look at what will drive that extra $2000 per account. Obviously we have to do more training. So we’re going to have to do something more to produce those results. But maybe we don’t have enough technology or people or content to make that happen.
So you must decide what you’ll need spend to achieve your goal. Say you’re prepared to spend half of the incremental return – in this case $1,000 per account – to achieve your ROI of $2000 more per account.
Or you might say you want to invest $1900 per account. However, your CEO pushes back and says you don’t get any additional budget. So you have to figure out how to increase training participation without spending more money. Fine. $0 investment. You’ll use free software and hire a contractor from Upwork.
Good luck with that!
Right. It could happen. And the final step in the business case has three parts:
- A clear action plan
- A staffing model
- A fairly detailed forecast
Could you briefly walk us through those elements?
Sure. First, outline specifically everything you must do to execute your plan.
For example, say your strategy to train an extra 2000 customers depends on making more educational videos. However, you don’t have a video authoring tool.
So your plan starts with buying that software. You may also need to hire an instructional designer with video expertise. And so on…
Next, build a staffing model. It’s a huge mistake to simply tell your boss, “We’re busy. We need to hire somebody.” If you want support, you’ll need to identify who, when and why new resources must be added to achieve your goal.
For instance, when will you need to add an instructional designer to ensure that new content is ready to roll-out in September? And if you’re expanding live training, when will you need an additional classroom instructor?
You know the volume of training required, so you can work backward to map-out the resources you’ll need over time. This is the same way sales executives and call center managers develop hiring plans for business expansion. Even an estimate is helpful.
And the final step is the forecast, which is the demand part of your staffing model. This needs to reflect your expected training growth rate.
So, if you’re currently training 5000 customers a year, that’s 400 a month. To reach your new annual goal, you’ll need to add more customers, incrementally, each month. And as that growth volume cascades through the schedule, you can predict when new content, instructors and other resources must be in place.
How do you map content to this customer education business case? How do you choose the best content mix for your target ROI?
That’s where your spreadsheet model gets complicated. Actually, each row represents a different content approach. For example, if one row is a certification exam, who’s going to write the exam? That takes time, so you need to insert it.
As your program grows over time, you’re creating new content, whether it’s video or instructor-led or other content. Plus, you’ll need to account for maintenance of existing content, over time. It’s important to track each separately, so you can look at how each contributes to your goals.
So the model is continuously changing?
Periodically, you’ll need to evaluate and adjust your forecast. It’s important to remember that these models aren’t perfect. However, they should give you some basis for prediction and a reference point for conversations you need to have with your management team.
A strong business case also helps you to plan, so you’ll know with some certainty what you need to do in June of 2020, for example.
You’ll have to make a lot of assumptions. But guess what? That’s what math is.
And how often should you check your roadmap?
You’ve got to look at it regularly. I’d say at least monthly, because forecasting is typically based on monthly business cycles.
Is that when you should tweak it?
Right. Be prepared to adjust your spreadsheet a bit as you move forward, because it’s a model. It’s intended to shift along with your circumstances.
For example, you might find that you can buy courses must faster than your model originally estimated. Or much slower. Or maybe it’s March and you didn’t lock-in that second instructional design hire you expected in February.
So to keep the model up-to-date, you’ll need to redo your whole cascade down into the formulas through the rest of the year. Because when you change the variables, other things need to change.
Makes sense. So do you recommend any templates or tools to help organizations plug-in these numbers and manage this process…?
…For complete answers to this question and more…LISTEN TO THE FULL 30-MINUTE PODCAST NOW!
WANT TO LEARN MORE? JOIN OUR JANUARY WEBINAR
What exactly does it take to build a successful customer education program that naturally grows hand-in-hand, along with your business?
How can you win executive approval for this approach?
Join our Lead Analyst John Leh as he talks with customer education experts Khalid Shaikh of DataStax and Bill Cushard of Learndot about customer training models that make a lasting business impact.
You’ll get practical advice based on real-world examples, including:
- How to understand and evaluate scalable customer training models
- Must-have elements for a winning business case
- How to weigh costs and benefits accurately
- Common mistakes and best practices for sustainable growth
- Lessons learned from real-world programs
- Success metrics that matter most – and why
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