Building the Trust with Non-Technical Clients

/ / Career, Leadership

Edited by Carol Huang, Lin Ding

Speaker: Ken Blake (LinkedIn Profile)

Ken has over 20 years of experience leading, designing, and executing advanced analytic and research solutions for organizations across all industries, working both on the client and agency sides.

As a client consultant, Ken has sold and developed outcome-based data and analytic solutions for Fortune 500 companies, with a focus on analytic rigor while ensuring both actionability and operational feasibility.

In this article, you will read about Ken’s experience on where analytics teams stumble the most in building trust with clients and solutions on how to gain trust with them.

How Important Is Trust In The Analytics Industry?

Whether you are an analyst who is doing mostly hands-on work or trying to sell analytic solutions, building trust with those who are less technical than us is really important. By definition, the client is whoever your final stakeholders are. They are non-technical people for the most part, or at least less technical than you. You need to find an effective way to communicate with them, and ultimately, build trust.

Why is building trust important? Because you want to win new business and maintain client relationships. If you don’t have that trust with the client, you will not get very far in either of these two areas, no matter how talented your analytics team is.

Sometimes people may not realize that analytics people have no value without trust. In that case, clients are going to be much more hesitant to act on your suggestion, which essentially renders all of your efforts meaningless.

Two key indicators for evaluating trust with clients

        1. How often and how extensively your clients use the work you provide versus your analysis sits on somebody’s desk for a while, but it never gets action against.
        2. Avoid so-called “legless work,” which means if the analysis has legs, it makes its way around the client’s office.

What Does A Trusting Relationship Look Like?

Everyone understands their strengths and weaknesses. Most importantly, they openly acknowledge them. You will be specialists in your role, and you are probably dealing with a bunch of generalists. One sign of trust is where clients are letting you do what you are best at. And they are focused on doing what they are best at.

For analytics professionals, a big part of your role is to educate the organization or the clients as to what your role is, what your capabilities are, and the value you can provide. Because sometimes the clients may see you as those of the people that build dashboards for them. And they don’t know what else is possible.

Communication is efficient and purposeful. If you find that your conversations with clients are a little micromanaging, that is a typical sign of not enough trust between the two organizations. Ideally, what the clients are doing is from a communication standpoint where they are very purposeful in what they are asking for. They trust that you will take along with it.

All stakeholders describe the same shared vision. First, you ask your client about the articulation of what you are trying to accomplish together as a team? After getting that answer, you will ask your analytics team what their articulation of that shared vision is. If there is a significant difference in how they answer those questions, there is either a trust problem or will be one in the future.

Discussion: how did you build trust in your work?

Kathy, one of the audiences
Being an insight provider rather than just a reporter or a measurement person, figuring out how to come to the same page at the right time in the process which allows you to get to the same shared vision.

I have been working in three or four different teams across different places in a B2B tech company. I found a different level of success and getting that agreement on being an insight partner, and was invited to the conversation in order to be able to show each of these three points mentioned above.

Trusted partnership vs. a concerning one

When you hear the client say,

“We have this idea. Can you guys come as analytics people and come back with thoughts on it?”

You are having a good conversation with the client because that question shows that the client wants your input. They understand that the data and your insight are what is going to drive success.

When you hear the client say,

“Can you pull all these metrics for me?”

You know that the client is giving you a laundry list. In cases like this, your analytics team is not a real part of the solution but just hands on the keyboard. Because the client does not give you the context of what they are trying to do with it.

Why Is Trust Uniquely Difficult In The World That We Live In?

All competency teams struggle with gaining trust from their clients and business partners. When it is data analytics, you need to be particularly aware of the importance and difficulty of building trust.

Challenge one: dealing with multiple stakeholders with different objectives

Ideally, your stakeholders should be all looking for a solution to a business problem. However, there is some kind of confirmation bias. Some people essentially want the analysis to validate something that they have already concluded. In this case, they may have a harder time embracing conclusions that conflict with the one in their minds. Plus, there are people who are looking for ammunition to convince others. They have decided what the right decision is, and all they need is to convince their boss or other peers of their ideas.

Following different objectives would yield different types of analysis. Sometimes, you have all these three competing objectives within the same person that you’re dealing with. That is an even more complex and more challenging situation.

Therefore, an analytics person’s role is to consult with your clients and help them reconcile these three areas, to know what they are trying to solve. Sometimes you have to hold their hands through the reality that the analysis does not show what they thought it would. Creating that trust relationship is very important for that handling process.

Challenge two: dealing with generalists with different mindsets

Your audience could be the complete opposite of you who have very different skill sets and mindsets. It can be very difficult to build that relationship with somebody who comes from a completely different mindset.

Three common dialogues about when analytics teams stumble the most

1. “The data speaks for itself”

Frustration appears when we data analysts think that we have made a very clear empirical case for why the analysis is drawing a certain conclusion. However, we have to remember that it is not about the data speaking for itself. It is our job to make the data speak to a particular audience.

Data speaks in different ways to different audiences. We need to be that translation layer between the very technical world we live in and the marketing or media or creative or sales or product or organization we’re supporting.

Related article: How to Deliver Business Value with Data Analytics?

2. Too focused on “trying to be right” rather than “getting it right”

The client just doesn’t get it! The cartoon shown above is an insulting mindset that can pop into our heads. This one is critical and is a common trap that analysts fall into.

We can get so focused on proving with overwhelming evidence to show that our analysis is right. But we forget that getting it right is not really the goal. It should be about proving our point from the client’s perspective.

Like the prior points, know who your audience is, know what makes them tick, know how they consume data, and think about things. Then you translate and communicate it in a way that is most relevant to them. That serves as a critical piece to building trust.

3. Analysts can at times be hesitant to share bad news

Depending on what kind of organization you work in, you may get pressure inside your organization to not share bad news, especially if you are with an agency where you may be analyzing work that your company recommended. That is a sensitive situation that needs to be handled as a team internally.

Ken’s advice:
Start with an objective view of what is happening. Address the situation from a factual standpoint and present what your analysis is saying.

For example, you can talk from a referee or umpire mindset. Then you will see your job as calling in a ball or a strike, or to the football player, catching the ball before we hit the ground. The key is to speak up about the objective outcomes and offer diagnostic insights that we can use to improve and make the action more effective next time.

When your analysis results are going to be disappointing to a client or to your internal partners, you should focus on providing clarity as to what happened and providing a more subjective view of what could have happened with a modified approach.

Discussion: how to act when the analytics team stumbles?

Joseph, Director of Analytic Solutions at FocusKPI, Inc.
All these little stumbling blocks come up because analytics, in part, hasn’t understood the real root cause of what their client is trying to get at.

Here is one of the critical skill sets that a good analytics organization and analytics team should have: being able to listen to their partner and identify their challenges. Then understand why those challenges occur. The data analysis should go after why those challenges are occurring, rather than just what they want.

You are solving the client’s process problems, what lies beneath what they think is their issue. If you can get it, the second layer that they are not telling you directly (because they may not know it), then you will be able to remove the stumbling blocks.

Some of the most trusting relationships come from successfully sharing bad news with a client. It can also come from sharing something that they did not think was going to be true. If you can do that successfully, the client will realize that you are a partner that they can rely on to make things better.

The client looks at their partners as people who can help them get ahead in their careers or accomplish whatever they are trying to accomplish. The more we can get them to think of us as partners on that path, rather than potential threats to that path, the better off we will be.

I’ve seen some analytics teams like to define predictive modeling problems without even looking at the data itself or what other data they can collect. That is where they can stumble upon some problems.

Because a lot of times in analytics, we think the rest of the organization does things like that, where marketing comes up with ideas that aren’t fully vetted. And they do. But we can fall prey to that seeing problem by deciding what the solution is – before we’ve even figured out the viability of it.

So exploratory pieces are critical for any kind of analysis, especially for a model. In many cases, we get in their heads (stakeholders) as to what type of model and segmentation should be built – before we’ve really done the proper vetting upfront in terms of what’s possible and what ultimately we are going to be able to do effectively.

4 Ways to Gain Trust with the Non-technical Client

1. Start with the right mindset

No matter how much a client may nitpick your analysis or ask questions or challenge things that you think are obviously accurate, keep in mind that the clients need your expertise.

The client has hired you, or they are at least having a conversation with you about potentially hiring you. They want to have a trusting relationship as much as you do. So think of this as a partnership to get to a trusting relationship, think and speak like a generalist, not solely on the perspective of the analyst.

2. Think and speak like a generalist

When you have conversations with clients, even if you are not an active participant, don’t let your mind immediately go to what queries are. Instead, take a step back and think,

Is this really the time to start with that kind of a deal with the tactics of the mechanics? What business problem are they trying to solve? Why are they trying to solve it? What is the value of solving it? What are the different ways that we might be able to answer that question?

If you are more on the selling side, sell the outcome instead of the process. Think about our clients. We are typically not selling to analytics organizations but to marketers, salespeople, product people, and merchandising and finance organizations who care more about the outcome.

3. Spend a day with the creative department

Orient yourself around a competency group that you are not comfortable with and don’t know a lot about. You will quickly realize that you don’t always get it either. You may still get the analytics piece but know little about the creative and the marketing piece.

So think of that as a two-way street by having some empathy for your clients who are not as technical, and then you can work together to educate each other and develop a more productive relationship.

4. Being relevant: tell the client a story, not your own story

When presenting or building an analysis, speak to your clients in a way relevant to them.

If we need 50 slides to tell a story, use 50 slides. I would be surprised if you need that many. Your job as an analyst is not to share everything you did with the client but to share what you found and why it is important to them.

So brevity and being concise are a great way to be more efficient in your work and build trust with the client. It shows them that you understand what they are trying to accomplish, and you are speaking to them in their language.

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