Building Trust with Your Client as a Data Analyst
Building trust in a client-analyst relationship is critical for client satisfaction and the analysts’ branding. Projects can often end up with better results when both parties are engaged in a relationship with trust. What are some simple steps you can take to achieve that? As a student in the Master of Science in Business Analytics program at UC Davis, we get to partner up with an industry client to work on real-world analysis projects as a practicum project. My team has been working with BlueMatrix for a few months now, and I wanted to share some steps I found useful when building trust with our client BlueMatrix. These steps are easy-to-follow, and you can act on them right away.
1. Constant Communication
Trust is related to relationships, and communication plays a key role in establishing strong relationships. In the context of analysts and clients, both work-related communication and personal communication are critical. Analysts should update the clients on the progress made and issues encountered from time to time to keep the clients engaged. Constant communication also enables the analysts to collect client’s feedback and make changes to meet the needs as soon as possible. It is important to make sure the client knows that you are putting effort into solving their problems. In our practicum project, besides the weekly stand-up meetings we have with our client, we also try to interact frequently throughout the week in our Slack channel.
Besides work-related communication, your client should also know you as a person. Especially with the current pandemic, most of the communication is happening online which requires more effort to build trustworthy relationships. Just like Forbes mentioned in its article, “communicate more frequently than ever before” is needed to build trust in a crisis. My team made sure we had our cameras on during every Zoom meeting, and we started to add some small talks at the beginning of the meetings. People tend to trust the people they know better, so we aimed to build personal connections with our clients and make sure they feel comfortable working with us.
2. Effective Communication
One step further from constant communication is effective communication. The analysts should deliver messages in a way that is easy-to-understand for the clients. This will help reduce misunderstanding thus improve trust. The principles my team follow are “quantify findings when possible” and “use visuals instead of words”.
Consider the following two ways of addressing the same issue:
“I saw many null values in the data.”
versus
“About 30% of the Date column is null in this table.”
The second sentence is obviously much clearer and more effective than the first one. Therefore, quantifying findings when possible can make your messages more comprehensible and make yourself look more professional.
In addition, visualization has proven to be more efficient and effective than words[1]. In our Exploratory Data Analysis report to our client, instead of long paragraphs of words and numbers, we conveyed our key findings using mostly graphs and charts with bullet points on the side. This helped the client to identify actionable items much faster than if they had to read a report with thousands of words.
3. Incremental Deliverables
While working towards our major deliverables to our client, we realized the importance to bring smaller deliverables incrementally. During the data cleaning and wrangling stage, we had a lot more questions than deliverables to our clients. We recognized it as a potential issue and it might hurt the trust relationship with the client.
Our original plan was to do as much modeling as we could upfront and bring a final product by the end. However, we started to realize that there is no way for our clients to know if the final deliverable will be anywhere close to what they are expecting or whether the work we are doing right now is valuable to the company. Without incremental deliverables, no actions can be taken until the end and everything before that only exists in our imagination.
We took actions immediately after we saw the issue. We selected two team members to be in a separate team that works parallelly with the data wrangling team to build prototypes and incremental deliverables using the ready-to-use data. This way, we were able to speed up the process and also increase our client’s confidence in us.
4. Put Yourself in the Client’s Shoes
Finally, think from the client’s perspective helps to build trust as well. When your deliverables are considerate and actionable, the client will think that you truly understand their business and your analysis results are reliable. Here are some sample questions we have asked to make sure we put ourselves in our client’s shoes:
How relevant is this insight to the client’s business?
How costly would it be to use this in the future?
Can the client implement this in the future?
In an article published in the Journal of Management Development, implementation of recommended actions was identified as a common issue among consultant works. In our practicum work, we initially planned to deliver a dashboard using Tableau, but have later realized that Tableau is not the main visualization tool for our client. Instead, we will construct the same deliverables in Python, so that the implementation into the client’s system will be much easier.
In the end, communicating constantly and effectively, deliver incrementally, and put yourself in your client’s shoes can help you build trust with the clients, but being transparent and sincere from the heart is just as important. Truly value the relationship and be passionate about the work you are doing can make you take some of the actions listed above naturally. As we continue to work on the project with our client, we might encounter more difficulties, but we believe the trust between us and the client can help us go a long way.
