19 October 2021

Coaching Tech Landscape: Humans and Robots

Dani Johnson
Co-Founder & Principal Analyst

TL;DR

  • Coaching tech has exploded in recent years, helped by the pandemic, a stronger desire for connection, an increased need to engage employees, and the need to personalize learning.
  • The definition of coaching has broadened considerably, moving past a 1-to-1 conversation where a coach asks a coachee questions on the path to self-discovery; today it incorporates several different structures for coaching, including manager as coach, peer to peer, coaching circles, drop-in coaching, and coaching bots.
  • The majority (63%) of coaching vendors say that their revenue has grown steadily since 2018, even through the pandemic.
  • Coaching tech vendors are embracing new definitions of coaching, identifying the more rote, repeatable parts of coaching (such as matching coach to coachee, follow-up, and discipline) as well as creating software that takes the human coach out of coaching altogether.
  • Making sense of the diverse coaching tech space is difficult; however, based on information from 45 coaching tech vendors gathered through briefings and a survey, we have identified a model to help leaders make sense of the space.
  • Coaching tech falls along 2 main axes: human vs machine delivery, and utilizing internal vs external resources (including humans as well as models, data, and content).
  • Choosing the right coaching tech is contextual—what works in one org will not work in another. Understanding the purpose of the coaching initiative is key to choosing the right tech.
  • Orgs looking into coaching tech should ask the right questions based on their knowledge of their own needs and intentions; based on our briefings and survey, we provide some tips on the right questions to ask and areas to explore.

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Why this report, and why now?

We started paying attention to coaching technology well over 2 years ago. At first, it was out of curiosity: we were seeing vendors developing new ways to address a very old learning technique. Earlier this year, we took a look at our vendor database and realized that we had over 45 vendors claiming to provide some sort of coaching functionality.

Coaching technology has exploded. As orgs have developed a larger appetite for coaching, vendors have begun to think through what coaching actually entails and how some or all of those steps can be simplified.

Interestingly, as vendors have thought through what coaching entails, the definition of coaching has also morphed: it is no longer defined only as a 1-to-1 relationship where the coach utilizes tools and a methodology to help the coachee gain actionable insights that can help them perform better. It has expanded in ways that we didn’t imagine when we started this research.

To that end, it’s important to clarify that, in this report at least, we are making no judgments on what coaching actually means. Vendors sell what they believe the market needs; in our conversations with orgs, we also found varied definitions of coaching, as well as varied needs for coaching. So, when a vendor tells us they have coaching functionality, we take them at their word.1

This report was written to help us, and hopefully you, get a clearer understanding of the vast range of coaching technologies. As such, it answers the following questions:

  1. What are the major trends in coaching tech?
  2. What does the landscape look like, and what sense can be made of it?
  3. Who is playing in this space, and what are common and unique functionalities?
  4. How can orgs choose? What criteria should they use to find something that will work for them?

Let’s get started.

Major trends in coaching tech

Indeed, things have changed when it comes to the coaching world. In the last section, we mentioned that the definition of coaching has morphed, and that it is no longer defined solely as a 1-to-1 relationship between 2 humans. Technology is playing a bigger role.

And, as in other industries where tech begins to play a role (e.g., transportation: taxis, Uber and Lyft, self-driving cars, teleporting), things accelerate quickly. In the case of coaching, several things helped with that acceleration, including the pandemic, a greater focus on the employee experience, fear of the Great Resignation, and the promise of the ability to scale something that used to be just for top leaders, so it’s available to more people in the org.

What, exactly has changed when it comes to coaching tech? Our data and briefings with vendors pointed to a few attributes.

More coaching tech

First, there’s just more coaching tech, both in terms of players in the space and revenue being earned. We mentioned that our own vendor database has grown to over 45 vendors saying they have coaching functionality. We are seeing that growth in stand-alone tools as well as in add-on functionality in learning and performance tools.

Additionally, when we asked vendors about their revenue growth in the past 3 years, the majority of them, or 63%, said that their revenue has grown steadily (see Figure 1).

Figure 1: Revenue Growth of Coaching Tech Offerings since 2018. | Source: RedThread Research, 2021

A broader definition of coaching

More organizations are offering more coaching to more employees. Whereas coaching was once reserved for top leadership (or those with severe behavioral challenges), orgs now understand that there are benefits to coaching more broadly.

To accommodate the uptick in demand, coaching tech vendors are thinking about coaching differently. Our briefings and surveys surfaced several flavors of coaching, including:

  • Coaching on demand: Employees leverage expertise of an external or internal coach to work on a specific challenge at a specific time
  • Managers as coaches: Managers are trained and supported with platforms that can create accountability and discipline around coaching conversations
  • Peers as coaches: Peers utilize tech to pair up and participate in guided coaching sessions designed to bring clarity to challenges they may be facing
  • Reverse mentoring and coaching: Younger employees are matched with more experienced employees to share viewpoints and insights that can help them lead better
  • Coaching circles: Tech helps employees with similar challenges to meet to talk through issues and receive feedback and advice from the group
  • AI or machine-delivered coaching: Technology takes the place of a coach, helping employees become aware of certain behaviors and providing insights and data to help correct those behaviors

The coaching tech vendors we examined support a variety of these different coaching configurations. The tech they offer can help orgs to scale coaching, making it more cost-effective and helping leaders make a business case for increased coaching.

Coaching in more areas

Another trend we’re seeing in the coaching space is a broader range of topics offered by coaches and coaching tech. Whereas coaching used to only include performance or business coaching, new subjects are becoming more common. Figure 2 illustrates the topics that coaching tech vendors are currently focusing on.

Figure 2: Number of orgs polled that provide coaching, by topic | Source: RedThread Research, 2021

 

Not surprisingly, coaching follows some of the trends we’re seeing in the people space in general. Business and leadership coaching remain predominant, but wellbeing has crept in, as has Diversity, Equity, Inclusion, and Belonging (DEIB), both spurred by the pandemic and by the social justice movement.

Coaching on DEIB and wellbeing have both grown, spurred by the pandemic and by the social justice movement.

These new topics also speak to the fact that coaching is being provided as a benefit to individual employees. Health & fitness and financial in particular do not necessarily improve org performance; rather they are being offered to engage employees and help them eliminate stress and avoid burnout.

New things tech can do

Finally, there is more functionality. While earlier coaching tech focused on streamlining tasks associated with coaching (finding and paying coaches, facilitating conversations between coaches and coachees, and matching coaches to coachees), newer tech goes beyond those traditional functions to include aspects of AI, coaching without humans (machine delivery), integrations with work tech, nudges, and absorption of work tech data to make coaching algorithms better. We’ll talk a lot more about functionality in subsequent sections of this report.

AI, machine deliver, integrations with work tech, nudges, and more are changing the way orgs are offering “coaching” to their employees.

A model for thinking about coaching tech

Classifying coaching tech has been one of the most difficult HR tech projects we have ever taken on. Because coaching now has a much broader definition and because we are seeing a lot of new functionality, coming up with a picture that adequately describes what is going on has been a challenge.

That said, in looking at the tech and characterizing how orgs are making decisions about coaching tech, there appear to be 2 major factors driving decisions about coaching.

  1. Resources: Are resources available internally to support a coaching effort?
  2. Philosophy: Does the org believe that humans are necessary to deliver coaching?

There are many, many other questions that define what type of coaching tech orgs are looking for, which we’ll address in the final section of this report, but the above 2 factors seem to be the primary drivers. If orgs develop clarity about those 2 things, they can narrow down their coaching tech options significantly.

When we plot those 2 factors against each other, we get the 4-square shown in Figure 3 below, which gives us a helpful way of classifying coaching tech solutions.

Figure 3: The coaching tech landscape | Source: RedThread Research, 2021

 

This model divides the coaching tech landscape into 4 distinct quadrants:

  1. Quadrant 1: Human coaches, external resources. Coaching tech vendors in this quadrant match external (usually professional) coaches with internal coachees and provide tools and a platform to support the coaching relationship.
  2. Quadrant 2: Human coaches, internal resources. Coaching tech vendors in this quadrant match internal coaches with internal coachees and provide tools to support the coaching relationship.
  3. Quadrant 3: Machine coaches, internal resources. Coaching tech vendors in this quadrant leverage org-supplied data (often from other work systems) or provide tools to help coachees self-guide to receive insights, nudges, and other aids, often without the involvement of a human coach.
  4. Quadrant 4: Machine coaches, external resources. Vendors in this quadrant provide machine-delivered coaching based on their own frameworks or programs and offer up insights, nudges, and other aids as needed.

Obviously, not all vendors fit neatly within one quadrant. Most fall somewhere along each of the axes in the model. Figure3 places them roughly where we think they fall on both axes.

So, for example, CoachHub provides external coaches, and focuses exclusively on delivering coaching through humans. As a result, this vendor falls squarely into the upper right-hand quadrant of the model. Cultivate, on the other hand, uses internal data to drive its algorithms and includes no humans in its coaching, so the company is placed to the far left and bottom of the model.

Like many of our other models, up and to the right isn’t best. In fact, this model doesn’t define a best at all. Since coaching tech varies greatly, and since no 2 orgs have exactly the same environment and goals, defining an objective best isn’t just impossible – it’s not very helpful. This graphic, as well as the rest of this report, is descriptive and crafted in a way to help leaders choose coaching tech that will best meet the needs of their particular org.

The next sections are organized around each of these 4 quadrants. For each quadrant, we’ll share some of its characteristics and some of the common functionality. We’ll also share some of the more interesting functionality some of the coaching tech vendors provide. Finally, we’ll look at some of the best use cases for coaching tech in each quadrant.

A caveat: while we classified and identified many, many vendors, we’re sure that we missed some. The next sections highlight what some particular vendors are doing, but are written broadly enough to give you enough information to make good choices about solutions that are not included in our assessment.

Quadrant 1: Human coaches, external resources

The first quadrant (upper right) includes coaching tech that matches external (usually professional) coaches with internal employees and provides a platform for continued interaction between coach and coachee.

Figure 4: Vendors identified in Quadrant 1 of the Coaching Tech Landscape | Source: RedThread Research, 2021

 

This, undoubtedly, is the most traditional way to think about coaching—and consequently the tech that supports it. When most people think about tech to help with coaching, they think in terms of external coaches being matched with internal employees. It’s the way coaching has been done for centuries. And it’s probably the simplest and most straightforward of the 4 quadrants.

Common functionality

Coaching tech orgs in this quadrant share a lot of the same functionality. Of course, there are differences, and those differences could make a big difference in how the tech may function in a given company. But understanding what is common to vendors can help you make better purchasing decisions. We discuss some of these points of commonality below.

Platform for communication

One of the main functionalities in almost all coaching tech solutions in this quadrant is provision of a platform—that is, a place for coaching to happen. Platforms offer a place for the coach and employee to meet and a way to document agenda, goals, and topics to be worked on.

Coach matching

The majority of coaching tech solutions in this quadrant also offer a way to match coaches and employees. Solutions falling in this quadrant generally believe that the coach/employee relationship is critical to success; thus, matching is an important functionality. In the solutions we looked at, matching primarily happens in 2 ways:

  • Artificial Intelligence (AI). Many coaching tech solutions tout AI matching—utilizing algorithms to find the best coaches based on the employee’s needs and the coach’s expertise. Note: While we didn’t dive too deeply into the AI algorithms of individual coaching tech solutions, we do know that AI is a very buzzy word and apt to be used in many ways. Those looking for solutions should ask some pointed questions about the algorithms and how exactly they function.
  • Matching Assessments. Many solution vendors take a more tried-and-true approach to assigning coaches by asking employees exactly what they’re looking for through short assessments, and then matching coaches to them accordingly. As with AI, we encourage additional questions about matching, as well as ability to personalize the questions on which employees and coaches will be mapped.
Competency assessments

One of the beauties of coaching tech is that it can standardize coaching practices across the organization. Many of the solution vendors in this quadrant accomplish that by way of assessments. Assessments run the gamut—from asking a few questions about what you want to focus on to asking for a complete 360° assessment by the coachee, to get a sense of what their development areas are. This information is available to the coach and the coachee so that they can work together to strengthen those areas.

From the org’s perspective, standard assessments and a common development model can unify coaching initiatives and provide a consistent vocabulary, particularly if coaching is being used to get a group of employees (leaders, say) to have similar behaviors. It also provides the possibility of analyzing rolled-up coaching data for all participants.

Coaching tech vendors in this space tended to utilize their own models and data to create these competency assessments.

Data

One of the big promises of coaching tech, which is not unique to this quadrant, is the availability of valuable data that can be used to evaluate the success of the coaching and the progress of the coachee. Until coaching tech was born, most orgs were reliant on self-assessments, satisfaction surveys, or their faith that the coach was doing a bang-up job. Now, almost all coaching vendors offer some sort of metrics for this purpose (although they can be sparse in some areas).

At the very least, orgs are now able to understand coachees’ level of engagement with the coaching initiative and a general sense of how coaches are performing. For many orgs, this is enough, both because it’s likely more than they have had in the past, and because of their concerns about privacy and confidentiality in the coach / coachee relationship. Orgs choosing this kind of tech tend to be less worried about the granularity of the data than in some of the other quadrants we explored.

That said, with some coaching tech solutions, particularly those utilizing standardized models across all orgs, data about topics being worked on could be rolled up to the manager, department, and org levels to give orgs more information about the types of things that were being coached.

Coaching quality

Many of the vendors in this space are also concerned about the quality of their coaches, and have therefore put interventions in place. This usually takes the form of a consistent coach onboarding process, vetting (many mentioned ICF-certified coaches), ongoing training, and quality checks. Because coaching tech keeps tabs on satisfaction data with respect to coaches, it is easier to intervene earlier when things are not going well.

Common coaching tech functionality for Quadrant 1 includes platforms for communication, coach matching, competency assessments, data, and ensured coaching quality.

Things we saw and liked

We found it interesting that coaching tech solutions in this quadrant understand the market and some of the threats to more traditional coaching. Coaching tech solutions that leverage external coaches understand that it is an expensive solution that most orgs are going to reserve for high-potential employees (HiPos) and present and future leaders.

Even so, one of the strengths of coaching tech is its ability to offer coaching to more people in the org. Within this particular quadrant, coaching tech solutions are facing constraints to their ability to attract and retain well-qualified, external coaches; in response, many are creating functionality that helps orgs to scale or show value beyond simplifying the administrative aspects of running a coaching initiative. Some of the features we liked are outlined below.

Alignment with existing leadership initiatives

Pluma (recently acquired by Skillsoft), among others, offers the flexibility to upload an org’s leadership model and customized 360, and provide coaching to leaders with respect to that model. This could be particularly useful in situations where orgs have well-established leadership development programs and frameworks, and want to ensure that any coaching initiative is aligned with them.

Human coaching for specific topics

Many of the coaching tech vendors in this space appear to have recognized new needs in the marketplace and created particular “programs” to address those needs. In an earlier section, we identified several coaching subjects. While the majority of orgs still seek coaching to help with the classic topics of leadership and business growth, many are interested in several new coaching areas.

These new areas, including wellbeing and DEIB, can be slightly more programmatic than the more traditional areas, and can therefore be more easily standardized. This has allowed coaching tech solutions to provide consistent coaching topics and additional resources to help orgs struggling with how to address some of these topics.

For example, CoachHub saw a need for leaders with better Diversity, Equity, Inclusion, and Belonging (DEIB) skills; it created a framework that can be used to build those skills throughout the org.

Another example is Betterup’s recent foray into wellness and mental health (in fact, if you check out their website, coaching is now de-emphasized as they move into these new topics). Their coaches now include therapists and peak performance experts, with the goal of ensuring that employees receive the individual care they need to be at their best.

Just-in-time or drop-in coaching

Torch.io has worked with clients to create drop-in coaching—opportunities for employees beyond traditional HiPos and leaders to schedule time with professional coaches on an as-needed basis. This time can be used to role play an upcoming situation, discuss career moves, or talk through business challenges.

 

 

Early career coaching

One of the newer applications for coaching is serving those early in their careers. From an individual perspective, an external perspective can be valuable as younger employees consider their first big career decisions. From an org point of view, coaching is increasingly being used as an engagement tool.

One coaching tech solution focusing specifically on early career is The Lighthouse. Lighthouse is a small company that leverages grads from top MBA programs to provide one-off coaching sessions with early-career coachees.

Best used for

In our initial conversations with org leaders, we found that many are looking at several different technologies for different types of initiatives. Based on those conversations, our assessment of the best uses for technology in Quadrant 1, which uses human, external coaches, are:

Ensuring higher-quality coaches with credentials

Many of the tech vendors in this category tout the quality of their coaches; many refer to ICF (International Coaching Federation) certifications and/or years of service. These vendors place a very high value, not only on tech and scaling, but also on ensuring a quality experience.

A human touch

With the pandemic has come a push by many organizations to provide more, not fewer, points of human contact. Vendors within this quadrant also highly prize human interaction (some going so far as to claim that unless coaching involves humans, it’s not actually coaching). For orgs looking for more human touch, vendors in this quadrant may offer the best solution.

Offloading administrative tasks

Before this type of coaching tech existed, many orgs relied either on a binder full of bios of trusted coaches that they then assigned manually, or on programs run by outside consultancies or training firms. This type of coaching tech takes some of the administrative burden out of providing coaching by automating tasks such as matching coach to coachee, or ensuring continued interaction.

Quadrant 2: Human coaches, internal resources

Given that coaching is becoming an increasingly hot topic, it comes as no surprise that organizations are trying to provide the opportunity to as many people as possible. One of the obvious challenges is cost and scalability: offering coaching to everyone can put a fairly hefty dent in development budgets.

Coaching tech in Quadrant 2 addresses this issue by leveraging internal resources. In most cases, this takes the form of leveraging human coaches from among the employee population. Coaching tech solutions in this quadrant also tend to leverage internal or proprietary data, models, and content as well, rather than utilizing standard models provided by coaching tech.

In this quadrant, we also heard more about creating a “coaching culture” or teaching coaching skills more broadly, particularly to managers, rather than relying on traditional coaching relationships.

Interestingly, one of the challenges associated with creating a coaching tech landscape was the breadth of ways that vendors describe internal coaching. True, many stick to the traditional description of coaching: discussions between 2 individuals. However, we saw the most diversity in both offerings and users in this quadrant. This quadrant was also where most mentoring vendors make their appearance.2

Technology that falls within this quadrant is geared mainly toward either setting up an internal coaching program (without the use of external coaches), or creating a learning culture—usually by encouraging manager / employee development discussions. In our investigation of these vendors, we found they had 3 major flavors:

  • Coaching platforms, many of the same that offered external coaching services, configured to utilize internal resources instead of external coaches
  • Mentoring platforms that provide a way for continuous feedback and direction from mentors to be leveraged for coaching as well
  • Dashboards in skills, mobility, and learning platforms that provide information to managers about how employees are performing so that they can better coach them

Figure 6: Vendor identified in Quadrant 2 of the Coaching Tech Landscape | Source: RedThread Research, 2021

 

You may have noticed that our Coaching Tech Landscape shows several coaching tech solutions that hover between Quadrant 1 and Quadrant 2. These solutions have platforms that are configurable enough to be used to access either external coaches or internal coaches.

Common functionality

Defining common functionality in this quadrant is difficult because of the broad definitions of coaching used by the quadrant’s vendors. Aside from traditional coaching relationship (1-to-1 conversations where a formal coach asks exploratory and discovery questions of the coachee), we also observed several other types of coaching relationships, including peer coaching, manager coaching, coaching circles, drop-in coaching or just-in-time coaching, and reverse mentoring.

Several functionalities appear to be fairly standard across a number of the coaching tech solutions.

Matching internal coaches with internal coachees

For coaching tech solutions that focus on the 1-to-1 relationship between coaches and coachees, we saw the same sorts of functionality that we found in Quadrant 1. This is not surprising, since many of the players from Quadrant 1 can configure their solution to work for internal coaching pools, which can be helpful to orgs that want to move between external and internal coaches.

Coaching tech solutions in this quadrant generally match internal coaches and coachees in 2 ways: AI and matching assessments. We saw little difference in matching functionality as it was applied to either internal or external coaches; the only difference appears to be the coaching pool.

Platform for ongoing engagement

As in Quadrant 1, most vendors focusing on the 1-to-1 relationship between coaches and coachees also provide a platform for continued communication and discussion.

More integration, more nudges

Because of the internal focus and their broader definition of coaching, vendors playing in this quadrant are more likely to integrate with existing systems. Many identify integrations with work technologies (mainly Slack and Teams) to help coachees stay on track and check in regularly.

There are also vendors in this quadrant that provide more than just coaching tech (i.e., they’re a learning or performance tech that also does some coaching), and so more integrations to additional resources, assessments, learning platforms, and the like are also more common.

Access to additional resources

Many of the vendors in this quadrant provide access to additional resources or micro-learnings in order to enhance the coachee experience. This is not surprising, given that many of these are learning platforms with a coaching component; we do however, like the idea of extending the learning beyond the in-person engagement.

Several vendors also have onboard coaching resources as well, to provide training or help to amateur or manager coaches

Common functionality for many of the coaching tech vendors in Quadrant 2 includes matching internal coaches with internal coachees, platform for ongoing engagement, more integration, more nudges, and access to additional, usually internal, resources.

Things we saw and liked

Coaching built into other initiatives / Asynchronous coaching

Both Novoed and Intrepid offer coaching as a part of their cohort learning platforms. Both coaching tech solutions include video exercises with offline feedback, scheduling, and group coaching in their platforms.

Novoed provides a Coach’s Dashboard so that coaches can understand where each of the coachees in the cohort are and identify needs.

Figure 7: Novoed’s Coach dashboard | Source: Novoed, 2021

Depending on the program and need, Intrepid enables coaches to provide feedback throughout and are available to schedule 1-to-1 engagements with employees who want a little extra help or advice.

Figure 8: Intrepid's Rubric page | Source: Intrepid, 2021

Asynchronous coaching is used quite a bit in sales or other industries where the practice and delivery of certain skills is important. This technology allows employees to record themselves performing a task (a sales pitch, for example) and then receive video feedback based on a predetermined rubric.

Rehearsal offers an asynchronous coaching tool as its main functionality. It allows orgs to set exercises (sales is a big use case), then allow people to practice as many times as they would like with video, submit the video, and receive feedback from a coach who refers to a rubric. If orgs want, they can also allow other coachees to view, judge, and even upvote video practices.

Bongo (which, incidentally, doesn’t sell to end customers but is instead incorporated into other coaching tech solutions), also enables asynchronous coaching through video and rubrics.

Manager-as-coach dashboards

There are also a number of products that focus on providing information to managers so that they can better support their employees.

Degreed’s Skills Coach, for example, provides a manager dashboard that summarizes a team’s skills, as well as providing data on each individual, so that managers can plan the coaching for both the team as a whole and individuals.

 

Axonify and Qstream, both of which focus on front line workers, are considered learning tech but offer dashboards to give managers a sense of what employees are focusing on and where they may need individual coaching.

And Bridge, recently separated from parent company  Instructure, is considered both a learning and performance tool. It was also built with manager-as-coach in mind. It offers data visible to managers to help them provide better feedback and guidance about development and performance, and a platform for ongoing discussions. Bridge also offers a timeline of activity and a space for weekly check-ins to enable managers to act as coaches.

 

We are big fans of providing managers as much information as possible when they’re coaching employees. These dashboards provide employee development and skills data to managers, which can help them tailor feedback and guidance for further development or better performance.

Focus on DEIB

Many vendors spoke of the ability of orgs to use their tools to further DEIB efforts; many had stories about utilizing their platforms to further coaching and mentoring efforts among specific populations. Chronus was one vendor that stood out here—they pay specific attention to their matching algorithm to encourage more inclusive matching; they also provide a dashboard geared toward increasing diversity in mentoring relationships and are beginning to offer insights associated with industry DEIB benchmarks to help orgs make better decisions.

Peer coaching functionality

With the broader definition of coaching comes additional functionality. Imperative’s coaching tool, for example, provides a platform and guided discussions to help managers coach each other peer-to-peer. The platform and structure ensure that managers adhere to coaching principles (open-ended questions, for example) and that there is a place and prompts to continue conversations. Pairing managers together helps them reflect on how they perform and what they can do better.

Figure 11: Imperative’s manager peer-to-peer coaching tool | Source: Imperative, 2021

Best used for

Orgs utilizing coaching tech vendors in this quadrant generally have 1 of 3 goals for their engagement.

Scaling coaching to more people

Orgs that use the coaching tech solutions in this quadrant are interested in providing a human coaching experience to their employees, but want to leverage internal coaches in order to do that. The solutions in this space are enhancing the skills of existing resources and providing guardrails or guidance so there is more structure and consistency across the coaching experience.

Creating a coaching culture

This type of technology is also being used to help orgs build a coaching culture. In the wake of the pandemic, many orgs have realized (again) that their managers are not as strong as they could be. Many of these solutions have been implemented to give managers support and guidance around career coaching and difficult conversations.

Upskilling and supporting managers

The pandemic and related moves to hybrid and remote work settings have caused orgs to reevaluate the quality of interactions between employees and their managers. In many cases, managers are falling short. Fortunately, orgs are also recognizing that the shortfall isn’t due to lack of trying or desire, but rather a lack of skills and support. Many coaching tech solutions in this space are geared toward answering this need.

Quadrant 3: Machine coaches, internal resources

The bottom half of the coaching tech landscape focuses on solutions that mainly rely on technology or machines to deliver coaching. These tech solutions use information to drive prompts and help coachees think through how they’re doing and what they can do to improve.

The promise of AI or machine coaches is generally 3-fold:

  • It offers a fairly inexpensive and unlimited way to scale coaching to more employees
  • It solves one of the major challenges of coaching – consistent check in and feedback – that is difficult if relying only on the humans.
  • It offers a means of standardizing data – currently one very big hole in the world of coaching tech

In this quadrant, we start to see a departure from what is considered traditional coaching. Not only do we see more automated coaching systems that don’t rely on the humans (or augment what the humans are doing), but we also see more integration and interaction with performance and learning tech.

In fact, as we look across our HR tech research over the past 5 years we’re seeing much more overlap between performance, learning, and engagement platforms. Many offer consistent follow up, spreading learning over time, identifying ways to personalize experiences, and nudges for regular conversations with managers. These functionalities do overlap with what coaching has come to mean, so they likely have a legitimate claim to the therm “coaching tech”.

This does mean, however, that leaders need to be extra vigilant and ask lots of questions about the nature of the “coaching” offered. We mention this in the section dedicated to Quadrant 3, but this is also an important point for Quadrant 4. Do your homework. Ask lots of follow up questions (see the final section of this paper). We’re in new territory here.

We also think the use of machines that feed off internal data and provide valuable insights to employees will continue to grow as data gets better and it becomes more acceptable to use coaching data as employee development data.

Figure 12: Vendors identified for Quadrant 3 in the Coaching Tech Landscape | Source: RedThread Research, 2021

 

Coaching tech solutions in this quadrant rely heavily on internal data and resources. They often absorb information from other work tech to generate insights that are delivered directly to employees. They also often point to internal resources (via a learning platform, for example) that can augment feedback or insights.

Delivering this information directly to employees—sans manager or human coach—can sometimes take the sting out of feedback and provide data in a way that can be more easily absorbed by the individual.

As with Quadrant 2, we ran across several learning tech solutions that are also targeting coaching clients. As several of them do have coaching functionalities, we have included those that tell us they’re coaching tech, even if their main functionality is L&D tech.

Common functionality

Common functionality in this quadrant was a little harder to identify. From the survey filled out by coaching tech solutions, however, 3 common areas surfaced.

Digital or AI coach – nudges

Common to this group of technologies was that all of them have a digital component and do not require a human. Some vendors call this functionality a “coach on the shoulder” that provides information when it is most likely to be absorbed and used.

Most tech solutions provide this information through nudges—small insights or reminders to coachees, based on their desired behavior changes.

Integration with work tech

Most of the vendors in this group integrate in some way with work technology. This is used for both pushing and nudging, and to gather data on performance to help the tool get smarter, which makes for better insights. Common integrations are Slack, Teams, email clients (Google, Outlook, etc.).

Data and Information pushed down

Tech solutions in this quadrant tend to push information down to the individual rather than delivering it through a manager or coach. We saw a lot of dashboards and insights summaries as a part of these solutions, making the individual—the person most motivated and able to act—responsible and empowered to do so.

The majority of coaching vendors in this quadrant say their solution:

  • Provides data and information to coachees to help them understand their own progress
  • Rolls up data to manager, function, organization levels, etc. to help the org better understand challenges and areas of focus

Because it is integrated with existing work and HR tech, data associated with these types of coaching tools tends to be better and slightly more granular. We observed that these tools have a greater ability to roll up results and provide individuals with progress data than solutions in either Quadrant 1 or Quadrant 2.

Common functionality in Quadrant 3 includes digital or AI coaches and nudges, more integration with work tech, and data being pushed down and provided to employees (rather than their managers).

Things we saw and liked

As we mentioned earlier, the bottom half of the coaching landscape is pretty new. As AI, machine learning, data, and comfort with sharing data about coaching gets better, we expect a lot of growth. Some of the differentiators that showed up in this quadrant include the following.

Team coaching

In most learning tech we have seen in the past few years, nudging has been used mainly as a way to help employees follow up on learning initiatives. Within this quadrant, nudging is being used in a much more sophisticated manner.

Humu, for example, uses nudges to help teams improve. After understanding the goals of the team and how they’re working toward them, Humu utilizes a series of actionable nudges that promote continuous improvement. Nudges are personalized to the individual team member, but take into account the team and goals, so that teams can help each other execute.

Because nudges happen regularly, teams have opportunities to reflect and respond, allowing the tool to gather and integrate more data to better target nudges.

Digital coaching to optimize live coaching sessions

We also ran across tools that utilized machine delivery and AI to simplify the human coaching element. Sparkus, for example, has an onboarding and self-coaching component that requires those interested in having a coach to think through what they want to accomplish and what help they need in advance. This prework has a couple of benefits.

First, it helps orgs understand the level of commitment of coachees; since they are not assigned a coach until they finish the self-coaching component, orgs can quickly understand who is serious about the experience and who isn’t. Second, it helps to minimize the amount of live coaching needed. One challenge many orgs have is understanding when a coaching engagement is finished.

The self-coaching component helps the coachee and the org to bookend the human coaching engagement, optimizing the number of sessions with a live coach. This helps organizations scale because they are able to offer a finite number of coaching sessions to more individuals.

Figure 13: Sparkus coaching onboarding screen | Source: Sparkus, 2021

 

AR/VR

While there aren’t many, we also ran across a couple of vendors that leverage augmented / virtual reality to help with coaching. Mursion, likely the most well-known tool in this space, provides an immersive coaching experience. Coachees complete a simulation where they need to handle a difficult conversation (our demo experience was about creating a safe place for employees with very different opinions to discuss whether a woman should be promoted).

Figure 14: Mursion’s Addressing Implicit Bias Experience | Source: Mursion, 2021

 

Mursion utilizes a combination of technology and real players (actors) on the back end to give an accurate simulation. While the experience from the user side is slightly animated, coachees have the opportunity to read body language, respond to tone, and evaluate all players in the scenario. It also provides a deeper experience than coachees can get with a static, linear role play, and accounts for some of the current shortfalls associated with tech simulations and AI.

Coaches on the shoulder

Cultivate is a great example of a tool that absorbs data from other systems—in this case, email—and provides feedback to managers about how they are communicating with their team members. It uses a combination of data and insights to make managers aware of behaviors and suggest ways to change them. For example, a manager may get a prompt telling her that she is sending less than 5% of emails to her team after work hours—which is good—but that prompt may also identify the individuals to whom she is sending after-hours emails.

Cultivate also offers ideas that can be tried immediately; in this case, onboard learning snippets can give the manager information on improving communication habits, adjusting priorities, or simply delaying sending messages until business hours.

Figure 15: Cultivate’s Manager Behaviors Dashboard | Source: Cultivate, 2021

 

Because the tool is integrated with a particular manager’s communication tech, the insights as well as the feedback are personalized. Because the coaching is integrated into the flow of work, managers are more likely to be able to use that feedback immediately.

Emplay is another coach-on-the-shoulder type tool. While its current strength is in sales, it is also branching into manager training. Emplay has the philosophy that successful coaching is a combination of sharing the right information and instilling discipline.

Figure 16: Emplay’s Coaching Dashboard | Source: Emplay, 2021

 

Emplay provides coaching in 4 areas: First, it can surface experts within the organization based on the experts’ assignment and data recommendations. It can also use conversational tech to ask questions that prompt coachees to reflect and find answers to their own questions. Third, Emplay surfaces behavior patterns in salespeople that can provide insights that can help them close deals faster; finally, Emplay can absorb long-form content and then utilize it to respond to queries via Teams and Slack. Emplay also creates dashboards and provides access to both manager and coachee for more insightful discussions.

Best used for

Because the tech falling in this quadrant is not traditional, utilizing this type of tech requires a non-traditional mindset. While coaching of this type will likely never fully replace human-delivered coaching, it does provide some unique opportunities that have yet to be solved by human coaches. We see 3 major use cases.

In-the-moment awareness for creating new behaviors

One of the promises of machine-delivered coaching tech is the ability to insert coaching opportunities into the work itself. Many of the tools in this quadrant operate on of the assumption that making people aware of their behaviors is the first step in helping them to modify their own behaviors.

Support of other initiatives

Because of its ability to provide in-the-moment data and insights, this type of technology may be very well suited to reinforce other types of learning, performance, or change initiatives. For example, once information about behavior has been shared explicitly (manager shortcomings, for example), a tool from this quadrant may be very helpful in drawing attention to unconscious behaviors in the work flow.

This type of coaching tech may also be helpful in providing common language and expectations for initiatives such as DEIB and extending the useful life of initiatives; regular reminders or opportunities to practice can reinforce principles learned earlier and build skills for using that new knowledge in the context of work.

Scalability

Finally, as with every other quadrant, one of the primary purposes of these tools is to scale. Machine-delivered coaching, while not as personal as human-delivered coaching, is infinitely scalable and fairly inexpensive. Organizations looking to provide something may be able to start here.

That said, machine-based coaching, particularly in this quadrant, does not provide the human touch and may not elicit the positive reactions or engagement of employees whose org invests in a real live coach.

Quadrant 4: Machine coaches, external resources

As with the vendors in Quadrant 3, those in Quadrant 4 rely heavily on machines for delivery of coaching. However, they also utilize external resources—meaning coaching insights are based on external data, models, usually proprietary, and additional content that can be used by coachees for extra growth.

Figure 17: Picture of the quadrant and all the players | Source: RedThread Research, 2021

 

Orgs taking advantage of coaching tech solutions in this quadrant are generally looking for a solution that scales very easily and has some programmatic aspect. As this type of coaching tech generally uses proprietary models and resources, it can be seen as more of a turnkey solution than coaching tech in some of the other quadrants.

Common functionalities

The common functionalities in this quadrant are not surprising: machine delivery, and the provision and consumption of data for the purposes of creating insights. We detail some of them below.

Digital or AI coach

Most of the technologies in this section pride themselves on providing insights to coachees with little or no involvement of a human. Digital or AI coaches work with existing data in organizations to provide those insights in ways and at times that can be most impactful to coachees. They may come via Slack, Teams, email, or other systems that are already used for work.

This quadrant distinguishes itself from the other quadrants by the fact that almost all of the tech in this quadrant uses humans to augment the tech, not the other way around.

Roll up data

As we mentioned above, one of the benefits of utilizing the same models and having access to more automated data is that it is easier to roll data up. A characteristic of many of these vendors was the ability to roll up data to the manager, function, and organization level, to help the org better understand the challenges and areas of focus.

Integration with HR systems

Vendors in this quadrant also integrate more readily with the HR systems that are already being used in an org. Because they are often using standardized models and data to drive insights, it may be easier for these coaching tech vendors to also standardize their integrations. In some cases, they may also be key to the functioning of their solution. We think this may be in its infancy as well – and there are privacy and ethics concerns that must be addressed – but linking coaching in with other HR systems, such as performance management, can help orgs tie coaching to broader goals.

Things we saw and liked

As with the other quadrants, there were several ideas or functionality provided by vendors that we found interesting.

Focus on wellbeing

meQuillibrium was one of the few vendors we spoke to whose solution provides coaching on well-being. meQuillibrium’s tool starts with an assessment based on their internal research. From there, coachees receive a personalized resilience program based on their assessment of how they deal with stress.

meQuillibrium provides data, feedback, nudges, activities, and content to help coachees understand what they need and then take care of themselves.

Figure 18: meQuillibrium’s personalized coachee homepage | Source: mequillibrium, 2021

 

Listening – AI speech coaching

Orai is one example of a AI speech coach that listens to the coachee as they speak and then provides feedback on pace, tone, and filler words. It has prompts for the coachee to practice extemporaneous speaking, a prepared speech, or a presentation. While it’s not perfect, we had fun trying this out. We found that it gave some great feedback on filler words and speed (2 of our biggest challenges).

Orai is a good example of where we see this quadrant going: humans were nowhere in sight; the tech leveraged natural language processing (NLP) and AI to provide actionable feedback and insights, and there were daily prompts over a period of time for continued improvement.

Figure 19: Orai’s web and mobile app UI | Source: Orai, 2021

 

Programmatic coaching augmented by group coaching

Pilot is a perfect example of a tech that utilizes humans to augment the machine coaching. Pilot focuses on managers and has utilized research and years of experience to identify the biggest challenges to managers. Its program walks managers through information, nudges, and activities to help them practice using new knowledge and skills online. It then augments this learning with planned group coaching events, where all coachees in a cohort join a call to receive extra instruction and get their questions answered.

Best used for

Coaching tech in this quadrant is probably the most experimental; several of the tools acted more like guided learning for the time being, but we see a lot of potential in this space. As AI and natural language processing (NLP) get better, we see the current coaching tech—and the possibilities for new coaching tech—getting better.

Orgs experimenting with some of these tools likely do so for 1 of 3 reasons.

Scalability

Because few, if any, humans are involved, tools in this space are usually infinitely scalable. It generally costs just a few dollars to add another user to this type of tool, compared to the hundreds or thousands of dollars it would take to add a user to a tech that uses human coaches.

Orgs looking for something that will meet immediate needs, or even act as a stopgap, may have success using some of the tools we’ve discussed.

Standardization

Orgs looking for standard off-the-shelf models for leadership, wellness, or other subject-matter coaching may find what they need in coaching tech within this quadrant.

Additionally, because vendors in this quadrant leverage the same model and the same resources across all users, data can be standardized and leveraged. With standardized data, these vendors will likely have an easier time improving the tool, its nudges, and its AI than those vendors that rely on human input.

Experimentation

Coaching tech in this quadrant is generally low risk. Because of that low risk, orgs that want to experiment with coaching, or more particularly machine coaching, might want to start here. Since the majority of tech here use their own models and there is not much on- or off-boarding cost, orgs may want to give a few technologies a try as they firm up their philosophy on coaching in general.

Choosing the right coaching tech for your organization

As with all of our tech reports, we try very hard not to make decisions for orgs or guide orgs toward particular solutions. We don’t give top 10 lists or indicate that one tech is better than another because, in all honesty, it entirely depends. Context matters. Culture matters. Goals of the initiative matter. What works for one org may not work at all for another. You can’t cheat off your neighbor.

In this final section, we provide some help to those looking for the right coaching tech for their orgs. We are hopeful that the 4-square model introduced earlier can help narrow down the choices at a high level. However, as we explored the tech, we found ourselves asking deeper questions to completely understand the solution, what it could offer orgs, and in what context it would be most appropriate. Even with the 4-square chart, orgs will need to be thoughtful about their own unique needs and their choice of a vendor to meet them.

The following sections outline 3 fairly general steps to take when looking for coaching tech.

1.     Define your purpose

The very first step in deciding which tech is going to work best for your org is to consider the goals of the coaching initiative. Different goals may require different tech.

For example, consider the following vignettes:

  1. You are trying to simplify the process of finding and assigning coaches. Right now, your org has to continuously vet coaches and then add them to a binder (yes, one of those things that holds papers), and then contract with each one separately. Coaching tech will help you to simplify the system you already have in place and ensure a level of quality you don’t have right now.
  2. Coaching in your org is seen as a coveted developmental experience. Since COVID, there have been fewer opportunities to provide rich, “special” employee development to HiPos and future leaders. You’re looking for a coaching tech that can help you scale. Your goal is to ensure that coaching is still seen as a premier experience, but with a lower cost point and wider availability.
  3. Your org has recently been acquired and you find yourself working with the org development team from the acquiring company to build common ground and standardize management practices. You need to offer some sort of education / change management support / coaching to all employees who are manager level and above. You want to provide a low-cost, yet somewhat personalized experience that can provide insights to those managers and help them develop a shared vocabulary and understanding of management practice.
  4. You’re trying to create a coaching culture. Rather than looking at coaching as something that only certain individuals get, you want to create a culture where peers can coach peers and managers can coach employees. You know that consistency and discipline are the keys to making this happen, so you’re looking for a tech that can help provide the necessary structure.

Tech appropriate for one of these scenarios may very likely not be appropriate for one of the others. The goal matters. Coaching tech, just like any other learning tech, has to fit the situation and the ultimate desired outcome.

It’s important for leaders to understand the purpose for their coaching initiative – it can greatly affect the type of coaching tech solution they should choose.

Orgs may also find themselves in situations where they have more than one purpose at any given time. Unfortunately, we found no single coaching tech that can meet all of the different coaching needs an org may have. Orgs may need to choose 2 or 3 to serve the needs of different coaching initiatives.

2.     Choose a quadrant

We hope that the major themes with coaching tech that we’ve described so far will help you narrow down the search for your particular initiative. To determine which quadrant you may want to consider exploring further, ask yourself a few questions:

  • Human vs. machine?
  • Internal vs. external resources?
  • Scalability?
  • Control?

Figure 20 provides the bones of the Coaching Tech Landscape. The double-ended arrows represent the 4 questions posed above and can guide you toward the quadrant you should be considering, depending on where you fall on each line, and we provide more detail about each question below.

Figure 20: Vetting questions for vendors | Source: RedThread Research, 2021

Human vs. machine?

Do you understand your org’s tolerance (or acceptance) of tech? In some organizations, coaching is seen as ONLY a human activity, while in others, scaling with tech is viable and jives well with the culture. Understanding where your org lies on that spectrum can help to determine which quadrant you should be looking at. Vendors in the upper part of the Coaching Tech Landscape model rely more on human coaches, while those in lower part rely on machine-delivery coaches.

Internal vs. external resources?

Do you have the resources to launch the coaching initiative internally, or will you need external resources? When you consider resources, think not only about humans, but about models, data or benchmarks, and content as well. Vendors on the left-hand side of the Coaching Tech Landscape tend to use internal resources, while those on the right rely on external ones.

Scalability?

How broad is the reach of the coaching initiative? Will it affect only a small cohort of employees, or is your goal to make coaching widely available? Machine-delivery coaching tools are much more scalable than human coaches.

Control?

Does your coaching initiative require that all coachees are coached using the same model or adhere to the same leadership traits? Do you want to determine what data and content is used, or are you looking for a vendor that will provide data and benchmarks, coaches, and models? Vendors on the left-hand side of the Coaching Tech Landscape tend to offer more control to the org.

3.     Vet, vet, vet

News flash: Vendors can’t or don’t always do what they say they can do. Many of the orgs we have talked to about their use of coaching tech have been disenchanted by the difference between what they thought (or were told) the tech could do and how it actually worked in the context of their orgs.

While there is absolutely no guarantee ever, and while there is much to do inside the organization as well to make sure the tech integrates well with other systems and processes, we’re very big proponents of vetting vendors to get the one(s) that make success the easiest. We spend a good one-third of our professional lives talking to vendors, and almost all of them will tell you that we ask an obnoxious number of questions. So should you.

The best advice we have for you? Ask lots and lots and lots of questions.

The following table identifies several questions that you may want to ask coaching tech vendors. While the list is clearly not exhaustive, we provide a set of questions that apply to any vendor, and then include several questions more specific to each quadrant. This list is by no means exhaustive. Understanding your goals for coaching tech will help you to identify others.

Figure 21: Vetting questions for each of the 4 Quadrants | Source: RedThread Research, 2021

In addition to quadrant-specific questions, those looking for coaching tech should also be concerned about the health of the companies they’re vetting. As a part of our Learning Tech Ecosystem research, leaders identified 5 things they look at when determining viability of vendors.

  1. Similar challenges. Vendors can refer potential customers to clients who have solved similar challenges using the vendor’s technology.
  2. Confidence of investors. While not always completely accurate, several leaders told us that they used the market to help them vet vendors. Understanding where startups were in the funding process gave them hints about the long-term viability of those vendors.
  3. Robust & innovative roadmap. Vendors should be able to speak confidently to their roadmap, and learning leaders should ask for it. Understanding the roadmap helps learning leaders to understand if the technology is moving in parallel with their organizational needs and enables them to assess the vendor’s innovation and ability to respond to the market.
  4. Longevity in the market. Leaders we spoke to were wary of very young vendors, worrying about their long-term viability. That said, some of the more forward-thinking leaders were also wary of vendors who have been in the market too long—worrying about their ability to react and be innovative.
  5. Evidence of partnering. Many leaders also mentioned using vendors as an extension of their team and a way to push forward and adopt new ideas. They look for evidence of partnering and problem-solving, not just providing software or content. As organizations continue to adopt an ecosystem point of view, it is getting more important to not just vet the tech, but also vet the vendors. Learning leaders should look for those who go beyond just providing services and can proactively help to solve problems.3

Wrapping it up

Exploring coaching tech and identifying a model to help leaders make sense of the space has been a pretty wild ride. We started out with some assumptions, all of which were blown to hell by the 3rd briefing. That said, however, we’re excited about this space.

Why? As with other areas on HR tech, the coaching tech space seems to be reinventing itself – which is remarkable given that the coaching tech space isn’t very old to begin with. We like that many of these vendors are experimenting – not just with what tech can automate from old models, but what new tech can do that has never been done before. They are, in essence, rethinking the very idea of what coaching is and how it can affect the largest numbe of people in the org.

In fact, as we have interviewed leaders for our sister report on coaching initiatives, we can safely say that coaching is one area where the tech vendors are ahead of orgs in how they’re thinking and innovating. We imagine that coaching tech vendors will continue to push orgs to think differently about coaching and we’re looking forward to seeing how that plays out.

Footnotes

  1. For a more nuanced and researched discussion on what coaching is, how it’s being used in orgs, what best practices orgs are using, and what the future of coaching holds, please see the companion report out November 2021: The (New) Wide World of Coaching.
  2. In identifying the players in the coaching tech solution space, we ran across several mentoring tech vendors; while we understand that coaching and mentoring is fundamentally different (and we address this in our other coaching study), we include the mentoring tech solutions in this study for 2 reasons: 1) many mentioned that their software could be used for coaching, not just mentoring, and 2) there aren’t enough strictly mentoring tech vendors for their own study.
  3. The Art and Science of Designing a Learning Technology Ecosystem, Dani Johnson and Priyanka Mehrotra, RedThread Research, 2019.

Written by

Dani Johnson

Dani is Co-founder and Principal Analyst for RedThread Research. She has spent the majority of her career writing about, conducting research in, and consulting on human capital practices and technology. Her ideas can be found in publications such as Wall Street Journal, CLO Magazine, HR Magazine, and Employment Relations. Dani holds an MBA and an MS and BS in Mechanical Engineering from BYU.

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