Tech Advisor Client Onboarding: What to Ask and What to Capture

Gathering the right information is a critical part of client onboarding as a tech advisor. Often, this search for intel has tech advisors playing multiple roles, becoming part consultant, part data scientist, and part investigative journalist.

Finding the right questions to elicit hidden insights from key users, managers, and senior leadership is a skill in and of itself but it’s also a necessary part of evaluating a client’s tech stack and understanding usage. However, with the proper processes, even this phase can be scalable, efficient, and, dare we say, enjoyable.

In this article, you’ll get tips on how to communicate with clients to find the important tech stack answers you’re looking for — which apps are working, which aren’t, and how to get the info you need faster and easier.

NOTE: This is part 4 of our ongoing series about the tech advisory process.

Part 1: How to Find and Qualify the Right Tech Advisory Clients
Part 2: How to Cut Your Tech Advisory Discovery Process from Days to Minutes
Part 3: Tech Advisory Pricing: Must-Know Quoting and Negotiation Strategies

How to Extract Information from Key Users During Client Onboarding

Let’s look at the most common ways that tech advisors get feedback from clients:

Surveys
Interviews
Usage data tracking

But before we get into these different types of collecting info, we have to talk about the differences between qualitative and quantitative data first.

Qualitative vs. Quantitative Data 🖥️

Qualitative data refers to any kind of data that is not represented by numbers. In other words, qualitative data is subjective, open-ended, and descriptive, and includes everything from written feedback to audio and video recordings. Survey of employees using the software is the most common source.

On the other hand, quantitative data is represented by numbered values. In other words, it’s objective — just the facts and figures, please. Accounting data is the best source to reveal the cost of applications, and single-sign-on (SSO) services like Google Workspace and Microsoft Entra ID are the best sources to gather actual software usage/login data.

An easy way to remember the difference between qualitative and quantitative is that qualitative data describes the qualities of something, while quantitative data shows the quantities (i.e. how much, in numbers).

Put another way, qualitative data answers the ‘why’ and quantitative data focuses on the ‘what’. And tech advisors should consider both data types to get the clearest understanding of a client’s tech stack usage.

Survey and Interviews 📒

Surveys tend to collect quantitative data (i.e. the numbers), but it also depends on the questions being asked because they can also collect qualitative data, too.

For example, a survey of multiple-choice questions and rankings on a scale from 1 to 5 would be quantitative due to the close-ended questions and numerical responses. Although, adding a few open-ended questions (such as “Can you please describe the challenges you face with the tools you use daily?”) to that survey would change it from strictly quantitative to a mix of both quantitative and qualitative data.

Conversely, interviews are primarily qualitative due to the open-ended nature of the questions, but they can also collect quantitative data if participants are asked to rate their experiences on a scale of 1 to 10, for example.

Compared to surveys, interviews provide in-depth answers and are generally more time-consuming, personalized, and often conducted on a 1:1 basis. Interviews are helpful to really get inside your client’s head and hear it in their own words, but you should also keep in mind that due to the smaller sample sizes typical of interviews, they are often more anecdotal.

4 Different Types of Surveys for Client Onboarding

Tech advisors love using surveys to collect info from clients and other key users because surveys are easy to administer, allow for larger sample sizes, and are typically faster to complete than an interview. Surveys are a great way to collect a large amount of information relatively quickly and there are so many types of surveys to choose from depending on the info you’re looking for, such as:

Usage frequency surveys
Feature utilization surveys
User satisfaction surveys
Pain point surveys

But if you’ve gone through the surveys and interviews and you still have questions, you might have to dig deeper into the data and usage tracking during client onboarding.

Usage Data Tracking: Analyzing Metrics 📊

If you’re still unable to decide whether to keep or remove an app after the surveys and interviews, it might be time to look at some metrics to help drive that decision. Of course, not all tech advisors will do the survey and interviews separately from the usage data tracking, as many tech advisors actually do a mix of the 3 (i.e. sending surveys, doing interviews, and analyzing usage metrics) concurrently to save time and maximize efficiency.

And if you’re trying to decide whether to keep or cut an app, we recommend looking at data such as:

Usage Metrics: such as the number of active users or task completion rates
Engagement Metrics: such as session duration, scroll depth, or CTR
Performance Metrics: such as load times or downtime

This usage data, combined with the info from the surveys and interviews, should help you find out what’s useful and what’s not.

Find the Useful Apps, Remove the Rest

When analyzing a client’s tech stack, you’ll want to separate the apps into what works and what doesn’t. But it’s usually not so binary or black and white because, as with so much in tech advisory, it depends.

In cases like this, we recommend separating the apps into three different categories — the Good, the Bad, and the Ugly:

The Good: The apps you’re keeping, aka the ‘core tools’ enjoyed by users and worth the expense
The Bad: The apps that may need replacing, updating, or removal, aka the ‘conditional tools’
The Ugly: The apps that need to be removed or phased out, aka the ‘ineffective disliked tools’ which are either not used or badly frustrating users

In other words, “The Good, The Bad, and The Ugly” is a catchy way to separate your client’s tech stack but basically, what we’re doing is separating it into the core tools, conditional tools, and risky tools.

Here’s how it works…

The Good ‘Core Tools’ vs. The Ugly ‘Risky Tools’

The “Good” and the “Ugly” (aka ‘Core Tools’ vs. ‘Risky Tools’) are less complicated and easier to separate. The “Good” is where you put the tech stack’s most effective and widely used apps for safekeeping, whereas “The Ugly” are shortlisted for removal.

If it helps, think of “The Ugly” as the bin for the outdated apps, tools that are no longer supported, and apps that pose a security or data risk.

It’s Complicated: The Bad, ‘Conditional Tools’ 💔

Where it gets more complicated is “The Bad” aka the ‘conditional tools’. Deciding whether to keep these apps is often determined on a case-by-case basis because there are redundancies, overlapping functionalities, or complicated integrations that make things more difficult.

For example, there may be an app that on paper should go directly into the “Ugly” category for removal, but what if a high-ranking manager who’s resistant to change single-handedly saves it from immediate removal? Or maybe there’s an app that is the bane of everyone’s existence but it’s so deeply integrated in the client’s systems and processes that removing it risks bringing everything down with it.

If you still have questions about which apps to keep, then it might be time to look to the client for more information.

How AppVentory Makes Client Onboarding for Tech Advisors Easy ✅

Lack of communication, redundancies, and incomplete data are common roadblocks when collecting information from tech advisory clients. Most of the time, setting clear expectations and automating parts of the process are easy fixes but when it’s not enough, AppVentory is here to help!

From initial tech discovery to the deeper questions to better understand your clients’ tech stack, here’s how AppVentory makes life easier for tech advisors:

Centralized data collection: Imagine all your clients’ data in one place, where you can manage your clients’ app subscriptions and monitor usage metrics to separate the good apps from the bad.
- What the business is paying for software is pulled from your accounting records such as QuickBooks or Xero to give you the most complete, accurate, and up-to-date facts?
- What employees are actually using is pulled from single-sign-on (SSO) services such as Google Workspace and Microsoft Entra ID so that you have the hard facts on what everyone is actually using.
Gather user feedback effortlessly: No more manual surveys! AppVentory allows you to automate surveys for feedback from your clients’ teams so you can quickly identify what’s working and areas that need improvement.
Identify tech stack gaps: Find out what apps your clients are missing or underutilizing and give expert recommendations to optimize their tech stack and increase efficiency.

Ask and You Shall Receive – And With Automation to Pull Accounting and SSO User Data – You Don’t Even Need to Ask to Receive

There’s an art to information gathering during client onboarding. Asking the right questions is key but it’s also about knowing when to follow-up and what to explore, which can uncover deeper layers that may not be visible from the surface.

A client’s tech stack might seem simple from the outside and it’s not until you dig deeper that all the overlapping functionalities, integration complexities, and data migration challenges become apparent — but this is where the real meat of tech advisory truly begins.

AppVentory helps tech advisors get there faster by streamlining the info-gathering process, automating manual processes that slow you down, and making it easier to determine which apps to keep, replace, or remove.

Does getting info from your clients sometimes feel like pulling teeth? Watch our free demo now to get a firsthand look at how AppVentory can help you build a better tech advisory process from the get-go.

AppVentory gives us confidence and control over software spend. We can clearly see which apps are being used, what they cost, and where we’re wasting money.