How do you communicate your analytics findings and recommendations to non-technical stakeholders?

Another important aspect to consider is spending time upfront aligning on the problem statement and involving stakeholders in the problem-solving journey. Rather than delivering a big final recommendation at the end, breaking your project down into digestible chunks and mini-decisions can be more effective. This approach provides ample opportunity to build a relationship of trust with your stakeholders and gain a deep understanding of their communication styles and expectations. Ultimately, the best final recommendation meetings are those where there are no surprises.

When I share analytics findings with folks who aren't tech-savvy, I use a mix of storytelling and visuals to make the data easy to get and interesting. It's all about connecting the dots between what the data says and real-world choices or ideas that can boost the business. I keep things transparent and explain methods in a simple way, so everyone feels confident about the insights and what to do with them.

Simple: the audience doesn't not speak our technical language. It is on the analyst or the technical expert to translate and relate

Understand that non-technical stakeholders are a resource for you. Their business knowledge, domain expertise, deep experience and intuition are an asset. Use their needs, questions, appreciation and even skepticism to critically evaluate and continuously hone the quality of your output. The most common need in communicating with these audience is translating between the business and technical knowledge. Spend time with them understanding their pain points to first uncover insights that are most valuable to them and gradually foray out to related recommendations to create a win-win communication model.

True. Narrative beats p-value. Meaning, technical fundamentals are not the win of the insights , but the expectations. Analysts have the responsibility to translate technical requirements into the business context. Remember a number is a conversation starter. Numbers bring people together.

Make sure to lead with your recommendations and action statements. Starting your presentation with the bottom line up front subconsciously instructs the audience to listen for the supporting facts and data that strengthen your recommendations. It allows them to build the case toward your ideas for themselves, as the rest of the information is presented. "This is what you should do. And now I'm going to tell you why..."

Lead people to the 'aha moments' when presenting analytics and data. In my days as an analyst, this was the biggest advice I took with me throughout my career. It's so much more impactful when people not only grasp the numbers but also connect the dots to those enlightening 'aha moments' that bring clarity and insight. When you focus on the key insight that led you to the results or main point you're sharing, others will do the same. This is why storytelling is so important even with data.

It is critical to be mindful of how the visuals and narratives align with the overall message, reinforcing it rather than distracting from it. While visuals try to make the data digestible, sometimes we tend to oversimplify leading to misrepresentation of the data. Consider a product that sells exceptionally well in December due to the holiday season, dominating sales with 40% share, shown in a pie chart. However, for the rest of the year, sales are low, making its annual share only 10%. A time series graph would better capture this seasonal fluctuation helping make informed decisions.

While using visuals is great, it is essential to consider the layout out of your report. Ensure the most important insights/metrics are the first visuals to be seen by the audience. The report/dashboard should not be containing all sorts of information, with data presentation less is more! Tip: before starting to create a dashboard, start by preparing a mock layout of metrics on a paper as this will allow you to visualize the story you’re trying to narrate through the report.

New analytics often represents a change in process, and change can often be viewed as a threat or a source of discomfort on the part of non-technical stakeholders. Its important to reinforce the potential value that Analytics can help to unlock, or how much easier Analytics can make those stakeholder's day-to-day, rather than articulating your project as a complete reinvention of internal processes. Also come prepared with concrete examples, such as the time to value analytics can bring versus existing manual processes.

- Simplify findings: Use plain language, avoiding jargon, and provide clear summaries of key insights. - Visual aids: Employ charts, graphs, and infographics to illustrate data trends and outcomes. - Focus on impact: Highlight how the findings affect business goals and decision-making. - Tell a story: Create a narrative that connects data to business objectives and real-world implications. - Anticipate questions: Prepare for potential queries by considering the stakeholders' perspectives and knowledge gaps. - Address objections: Acknowledge and respond to potential concerns with evidence-based counterarguments and alternative solutions. - Follow-up: Offer to clarify or provide additional details post-presentation.

Analytics is a never-ending process, especially if you are working in a b2c Space, where analytics is the Heart of a Company. You need to make sure that the insights you draw out, & and after those insights the Changes that are implemented in the strategy or Product; have resulted in outcomes that will help you also improve the quality of insights & and also keep you motivated in terms of the impact of your insights.

Some ideas to generate insights on the impact of analytics on decision making, focusing on tangible results: ?Come up with clearly defined key metrics, which should be linked to both benefits and costs : profits increase, impact on key business KPI's, report generation costs, etc. ?Implement continuous monitoring mechanisms to track and analyze the performance of analytics initiatives, as per those metrics. ?Establish feedback mechanisms to understand stakeholder experience with analytics offerings and make the necessary improvements.

Generally, we believe that complexity is a sign of intelligence or sophistication. However, solving a business problem using a difficult or complex methodology does not necessarily mean that it is correct. In other words, the solution to the problem cannot be more complex than the problem itself. Using data storytelling techniques to present information can enhance people's ability to remember and comprehend it. Utilize your analytics findings to craft a narrative that highlights the key insights, and focus on two metrics at most at a given point in time, tying them in with the story.

I would recommend to build a simple google studio dashboard with quantitative & qualitative approach Add limited metrics in the dashboard: For example: 1. Pageviews 2. Bounce rate 3. Traffic sources 4. Goal completion(if u have added manually, if any) 5. Conversions (if you would like to show) If non-technical audience is interested for specific geographic, u have the ability to add filters as well while preparing the dashboard.