Tuesday 29 January 2019
Tuesday 22 January 2019
Starting a Customer Education Program: What You Should Know
EDITOR’S NOTE: Occasionally, we invite learning community experts to share their advice with our readers. Today we feature a post by Adam Avramescu, Head of Customer Education & Training at Checkr and Co-Founder of the CELab blog/podcast. He also authored the new book, Customer Education: Why Smart Companies Profit by Making Customers Smarter.
Are you thinking about starting a customer education program?
Perhaps you want to support broader customer success or marketing strategies. Or maybe your support team spends so much time training customers that a dedicated position seems justified. Or possibly you want to differentiate yourself from competitors who might otherwise beat you to the punch. These are all valid reasons to offer standardized customer education.
As a specialist in this discipline, I’m seeing increased interest from organizations of all types, especially startups. It’s a smart move. Why? Because early investment in customer education helps young companies scale successfully.
My industry colleague, Dave Derington, agrees. In fact, we believe most organizations start too late. That’s why we recently launched Customer Education Lab – a website that helps professionals connect and share ideas about how to structure, launch and manage customer training and education.
In our first podcast episode, we discussed key factors to consider as you lay the groundwork for this function. Specifically:
1) When to invest in a customer education program
2) How to win support from executives
3) What to expect after launch
4) How to get started
To help you dig deeper, I’ve also outlined each of those topics below…
1) When to Invest in a Customer Education Program
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Many companies are operating in an ad-hoc prison that seems hard to escape. We call that “Ad-Hoc-Atraz.” Everyone provides their own version of training – from account managers and project leads to customer service managers and support reps. No two people use the same materials. And they redesign and customize training content every time.
Why is this such a common issue? Limiting beliefs are often the primary culprit. For instance:
“There’s not enough time.”
Everyone is so busy creating custom training for each customer, no one takes the time to develop standard materials. We would argue that you don’t have enough time not to invest in standardized training. Your team is actually wasting precious time answering the same questions and delivering the same core content over and over. If you take this burden off of each individual’s back, they can focus on issues that truly need custom solutions.
“We’re providing white-glove service by customizing everything.”
This is a commonly held belief in startup settings, but it usually isn’t true. You may be responding to whatever customers say they want, but it may not always be what they actually need. This puts your team in an endless reactive mode where they’re continuously taking orders, but not truly partnering with your customers.
“Our CSM should be able to do it all. They are our trainers.”
Think about that. Most likely you hired your CSMs and account managers for their relationship management or project management skills. Some may be phenomenal at delivering training, but unless you hired them specifically to document and facilitate training, you can’t expect them to be good at customer education tasks. In fact, they may not even enjoy these tasks, but they inherited the responsibility by default.
Startups shouldn’t expect to roll-out a full-scale customer education function on Day 1. But once your organization has hired more than a few CSMs, you’ll want to get ahead of “Ad-Hoc-Atraz” by delivering customer education in a consistent and scalable way.
How do you know if you’re ready? Calculate your all-in CSM headcount or cost-per-ticket totals for a specific timeframe. Then estimate the dollar value of the time your people spend on ad-hoc documentation and training during that same time interval. The total may very well be more than the cost of a full-time resource, already.
2) How to Win Support From Executives
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If you’re making a business case for customer education, we encourage you to speak the same business language your board uses. For example, many SaaS (Software as a Service) businesses focus on CAC/LTV ratio — (Customer Acquisition Cost vs. Customer Lifetime Value).
In contrast to selling on-premise software or other types of products in an upfront purchase transaction, SaaS models are usually based on subscription payments that accrue over time. This means vendors spend more on marketing and sales to acquire a customer than they actually receive at the start of a relationship.
In other words, SaaS companies must continue delivering value over the life of each customer, so total investment in their product increases over time. Ideally at some point, they earn back the money spent on CAC – and hopefully much more. Jason Cohen’s “smart bear” blog effectively illustrates this concept:
Although your senior executives may not care exactly how many hours of training you deliver or what kind of customer satisfaction scores you receive, they do care about your CAC/LTV ratio. They may also care about your product’s Time to First Value (TTV) for new customers. And they almost certainly care about your overall customer retention, customer expansion and churn numbers.
This means your customer education charter should be to help drive these metrics at scale, by enabling customers to adopt and use your product successfully in their space.
Luckily, there are industry benchmarks to help you establish some objectives. For example, research from the Technology Services Industry Association (TSIA) found that trained customers are:
- 68% more likely to use a product more
- 56% more likely to use more features and functions
- 87% more likely to work more independently (not submit as many tickets)
They also renew at a higher rate than untrained customers (92% vs. 82%). Customer learning platform provider Thought Industries paired these statistics with research from Bain & Company and found that a 5% increase in renewal rate increases profit by 60-228%. Analysis based on this kind of logic will help win the confidence of your senior decision makers.
Keep in mind that customer education is hard to measure. It requires an upfront investment that pays off over time. Most teams don’t recover the cost in their first years, even if they sell training at a premium. But if you measure training’s impact on product renewal leading indicators like increased adoption, you can build a strong case for establishing and maintaining a customer education team.
3) What to Expect When You Launch
When Dave and I launched customer education programs at Gainsight and Optimizely, respectively, we required about eight months to move from zero content to a fully functioning first version. Now at Azuqua and Checkr, we’re trying our hands at this again.
One thing we’ve found is that the process is iterative. You should expect to develop three or four “first versions” before a working program is in place.
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In addition, it’s important to be realistic about how long it takes to develop effective learning experiences. Bad training is created quickly. Good training takes longer, but it will serve you well over the long-haul.
Just how long should it take to create training content, anyway? In 2017 Robyn Defelice and Karl Kapp addressed this question in an article published by the Association for Talent Development (ATD). They found that developing 1 hour of content requires:
- 38 hours for traditional classroom training
- 28 hours for virtual instructor-led training
- 42 hours for passive elearning (no interactivity)
- 71 hours for e-learning with limited interactivity
Although average training development time has decreased in recent years (thanks largely to improvements in course authoring technology), it still takes longer than most people think!
We recommend starting with materials that are relatively quick and easy to prototype and update – for example, articles and recorded sessions. But it’s important to move toward learning experiences that scale with your business and evolve with your customers’ needs. So over time, you’ll want to add more interactivity to make the content more effective.
If you’re delivering ad-hoc training now, it’s probably not highly interactive. For example, to build a basic product tour, you may decide to insert a few Q&A slides into an existing feature deck. But this kind of passive introduction doesn’t actually engage customers with your product. It’s like trying to teach people to play the piano by telling them to imagine how great they’ll sound when they touch the keys.
Ad-hoc training tends to be more interactive for trainers. They need to do a lot of talking, and a lot of work to customize the content. But effective customer education is actually more interactive for customers. You’ll want to provide opportunities for participants to try their skills, reflect on their learning experiences and ask questions that are pointed and relevant to their situation.
4) Getting Started
If you’re just beginning to think about customer education, it can seem overwhelming. We recommend starting with these first three steps:
• Clarify what customer education looks like today
How do your customers learn to use your product, and who delivers this educational experience? Interview or survey your team to understand the role that CSMs, support reps, project managers and others play in delivering customer training and other educational materials.
• Quantify the time spent on ad-hoc documentation and training
How many hours do each of your team members spend preparing and delivering customized materials that won’t be reused for others?
• Define the business value metric that customer education should drive
Investigate the key performance indicators that matter most to your business. Product adoption rates? Customer satisfaction scores? Time-to-value? Net retention or renewals? Something else? Also evaluate the “leading indicator” metrics you can measure today and track over time to verify customer education progress. This could be something like support ticket volume or NPS scores.
Summary
Hopefully, this introduction has sparked your interest in investigating customer education strategies more deeply. For more details about how to start a program, listen to Episode 1 of CELab or check other content at Customer.Education.
As champions of customer education, our philosophy aligns with John Leh and the team of extended enterprise technology analysts at Talented Learning. We’re excited to share our experience and ideas with this community, and we welcome your feedback anytime.
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To Charge or Not to Charge? Strategies for Pricing Customer Training
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How much should customers pay for training? How should you choose the best price? And when does it make sense to educate customers at no extra charge?
Join experts John Leh, CEO and Lead Analyst at Talented Learning, and Barry Kelly, CEO and Co-Founder at Thought Industries, as they clarify the economics of customer education. You’ll learn:
- The true cost of content: free vs. fee
- Where the “freemium” fits in
- Why timing is a key factor
- How to test your price points
- The value of bundles and other packaging methods
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The post Starting a Customer Education Program: What You Should Know appeared first on Talented Learning.
Starting a Customer Education Program: What You Should Know original post at Talented Learning
Tuesday 15 January 2019
Podcast 17: Next-Level Learning Analytics – With Guest Expert Tamer Ali
WELCOME TO EPISODE 17 OF THE TALENTED LEARNING SHOW!
To learn more about this podcast series or to see the full collection of episodes visit The Talented Learning Show main page.
EPISODE 17 – TOPIC SUMMARY AND GUEST:
This is the first time we’ve welcomed a repeat guest to The Talented Learning Show. He’s that good! Today we’re talking about the brave new world of learning analytics with Tamer Ali, Co-Founder and Director of Authentic Learning Labs.
Tamer is a long-time educational technologist and learning systems expert who never stops pushing the envelope in extended enterprise learning and continuing professional development. He has designed, built and operationalized multiple learning software products, and is currently working on a next-generation learning analytics platform.
KEY TAKEAWAYS:
- Effective analytics is more than just data reporting. It involves interpretation and visualization of data in ways that are meaningful and useful for business decision makers.
- Business intelligence tools are not new. However, for multiple reasons, learning organizations and training content publishers have been slow to adopt authentic analytics.
- By leveraging technologies like AI, machine learning and the xAPI standard, innovative analytics tools are making it possible to measure learning in ways that create significant business value.
Q&A HIGHLIGHTS:
How do you define learning analytics?
We think of authentic analytics as a way to help learning and development organizations and training publishers track and analyze learning behaviors in a much more effective, efficient, turnkey way.
What challenges do you see with learning analytics?
When we investigated the market, we found many well-intentioned organizations that are creating really good educational courses and materials. But they haven’t been building a practice of learning measurement in their industry, concentration or field. Even though assessment and measurement of learning impact is a key objective of most initiatives, we saw very little tracking done in a methodical way.
What’s the current state of the learning analytics market, from your perspective?
Many organizations already have solid tools like Tableau and Microsoft Power BI. However, they often lack dedicated resources, or attention, or both. That’s the primary challenge we’re trying to solve.
For years, organizations have used LMS reporting to track things like course registrations and completions. Why should they add outside platforms like yours or Tableau?
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Yes, reporting is available in many learning systems. Over the last 10 years, it has become popular to pull that data into business intelligence applications like Microsoft Access or SAP Crystal Reports. However, those are fairly low-density, low-impact applications. In other words, the results may be tons of data displayed on maps or charts or spreadsheets. None of it provides quick, useful business insights.
That’s where authentic analytics is different. It’s not just about reporting, but about bringing in meaningful insights to guide decision making. It’s about trying to answer key questions our customers are most likely to ask.
For instance…?
It can be something like, “When is the best time of the year to market and promote courses in this category?” Or, “Which topics are attracting more (or less) interest?”
We’re trying to inform learning and development publishers with data-based intelligence used by other fields like marketing, finance and sales. Learning professionals have equal rights to insights. So we’re providing a specialized toolset. We didn’t invent analytics. However, authentic analytics has been missing from learning and development, so we’re trying to bring that discipline to this space.
What kind of people regularly use your product? What are their responsibilities?
Primarily there are three types of users:
- People who create and oversee learning material on an ongoing basis – This could be the platform administrator or someone who authors content directly. People in this role typically visit multiple times a day because the data is refreshed daily.
- The product owner – Anyone responsible for one or more educational products or training for a line of business. People coming in at that level receive the data either from the dashboards, or from an administrator, or go in themselves. Because of our license flexibility, they’re not restricted. They have full, direct access.
- The overall owner – The stakeholder who needs an executive-level dashboard and/or receives insights from the other two roles.
These people are typically in education or product management functions, but we also see some overlap with IT departments.
Why hasn’t next-level learning analytics been available before?
Well, these tools have been used for a while, but most have some sort of limitation. So, as people mature in their use of these platforms, they realize those limitations and they see a need for a more specialized solution.
For example, tools like Tableau and Power BI have license models that essentially restrict access to an exclusive set of people. Those organizations must provide access at scale, so it can be very expensive for training publishers or associations with multiple product owners and product managers. That approach becomes cost prohibitive.
I see…
Further, for a complete analytics solution, you must invest in hardware to house both the data visualization software and the data warehouse to compile all the source data. This is further complicated by the growing adoption of the xAPI standard for learning activity tracking. Use of xAPI increases the typical data set by multiple folds.
So what extra challenges does that add?
There are multiple related questions:
- Where do we put all this data?
- Who’s going to manage all this data?
- What tools do we actually need?
- Who is able to focus on interpreting this data and build a practice around it?
We’ve seen these issues in organizations of all sizes. That’s why we’ve created a toolset and we provide practitioners to support it. We consider ourselves a kind of BI team in the cloud.
That sounds great – but also complex. Do training teams in associations have the skills for this?
They don’t have the resources. They may have the wherewithal and the capabilities to build these dashboards, but they’re busy developing learning strategy, building new products and analyzing performance. That alone is an all-consuming full-time job. Some may look to their IT team for analytics support, but IT is also stretched with strategic projects. So, all too often, no one addresses the need.
And that’s where you come in?
Right. Our goal is to build a dashboard that is simple and intuitive enough for anybody to adopt very quickly. We want to empower users to develop business insights and make projections within seconds. That’s our core challenge. We take all of the unstructured source data and make sense of it in these dashboards, so you don’t have to do it.
How exactly does that work?
Here’s a recent case study: An organization wanted to justify its impact on assessments. They gave us five years of data – thousands and thousands of rows. If you imported this into an Excel spreadsheet, a typical business intelligence tool wouldn’t do any good. It would take weeks of analysis by experts in statistics, psychometrics and database queries.
But we aggregated those 30,000-40,000 tests attempts in a single visual line graph that interpreted performance on two lines – one represented pre-testing and the other, post-testing. So, in one half-page image, we summarized all that data and put the insights in their hands so they could drill down further. For example, they could uncover which tests work best (or not) within seconds, rather than spending hours and hours on the labor to dig deeper.
Earlier you said xAPI generates a massive amount of data, and that’s helping to drive analytics innovation. For folks who aren’t familiar with xAPI, what is that?
The X stands for “experience.” Really, xAPI is a radical leap forward from SCORM, the de facto learning content standard that ensures interoperability across platforms. xAPI says, “What if learning content includes much richer information?” It captures all of a learner’s activities within a course or a learning experience, and it shares all of that data with learning systems and other learning data record keepers.
So xAPI is a learning standard that doesn’t just focus on whether someone completed a course. Instead, it helps us reveal what they did within that course. xAPI adoption is still in process. It’s not yet widespread, but it’s certainly something that learning professionals should note and consider in their product development plans.
Got it. xAPI provides granular information that hasn’t been available before. But how do organizations make that useful? Do you analyze the data and make it useful for them?
Exactly. If you create custom courses with major authoring tools like Articulate or Captivate, they output xAPI data. We can capture and house that data, and present visualizations that make sense for your business and learning decision makers.
We also offer expertise to say, “Okay, you’ve created a custom course that is producing some very robust data. Let’s create a visualization that interprets that data in a meaningful way and we’ll make it available in your dashboards.”
What about incorporating data from business systems that have nothing to do with learning? Can you combine that operational data with learning data to see a connection with business performance?
Yes. Authentic analytics now extends beyond learning platforms to include complementary tools. So, for example, Google Analytics, Adobe Analytics, Salesforce CRM, and for associations, AMS platforms. Because we have access to that data, we can correlate and connect those data points.
For example, we can see what type of courses attract a particular kind of audience member. Or we can go the other way. For example, if sales performance dips, we can automate content recommendations in the learning platform to bridge the appropriate skill gap.
That’s the kind of powerful intelligence we can provide when we correlate data across platforms. This breaks down system barriers and avoids the isolated “island” nature of learning platforms, and begins to answer valuable business questions.
That makes perfect sense. So, tell me how artificial intelligence and machine learning impact this whole discussion?
Well, it’s not pixie dust anymore. A lot of people talk about these technologies at a high level, but they don’t follow-up with details or examples. That’s why they seem so advanced and out-of-reach to many people. But we use artificial intelligence and machine learning to do the heavy lifting in analytics. In other words, we leverage these technologies to put the burden on machines. And as they get smarter, they understand which feedback is positive and which is negative.
For example, machine learning lets us scale the text responses in evaluations and assessment, so we can score any answer categorically into positive, negative and neutral feedback. So, for organizations that sell or offer learning content to their members or customers, we know what’s favorably received, what’s not, what kind of feedback we’re receiving and what keywords or phrases are emphasized in that feedback.
And so it gets smarter over time. How does it get smarter?
As we capture more data, data informs the machine. And people who run the machine help it refine and polish the way we look at things.
For example, we’ve seen responses like, “No feedback at this point. But if I did give feedback, I would say that the instructor was great.” How do you score that kind of response? It’s a partial positive and a partial neutral.
We continuously learn how to refine things with algorithms that put the power of these machines on our side. The data is essentially the food we need. The bigger the data set, the better the performance of these machines.
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How to Capture Lifelong Learners: A Holistic Approach to Continuing Education
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Continuing education can be a lonely experience. Many of us must rely on ourselves to identify credible training sources, choose and consume content, earn certifications and demonstrate our value in the marketplace. But it doesn’t have to be that way.
How can continuing education providers make it easier for professionals to connect with the right resources and navigate through the lifelong learning process?
Find out from our panel of experts:
- John Leh – CEO and Lead Analyst – Talented Learning
- Tamer Ali – SVP Education – Community Brands
- Jacob B. Gold, CAE – Director, Education Development – Community Associations Institute
- Kevin Pierce, MAT – Manager, Digital Learning – American Academy of Dermatology
You’ll discover:
- Why and how to create a lifelong competency model
- How to support self-guided and directed content paths
- How AI helps enhance content recommendations and analyze results
- The value of digital badges and credentialing
- Pricing methods that lock-in long-term subscribers
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Need Proven LMS Selection Guidance?
Looking for a learning platform that truly fits your organization’s needs? We’re here to help! Submit the form below to schedule a free preliminary consultation at your convenience.
The post Podcast 17: Next-Level Learning Analytics – With Guest Expert Tamer Ali appeared first on Talented Learning.
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