Dashboard for your business performance and sales projections
Combine data from sales, accounting, inventory, marketing or other data sources to generate unique insights about your company.
Roles
As the only designer in a small team, I got to play more than just one role.
Product Designer
Talking to potential business oriented users who are usually responsible for a department.
Learning what the different metrics mean and how to best vizualise them.
Many iterations of wireframes to get a shared understanding of what metrics help tell the story and how the story should be told.
Project Manager
To help my stakeholders, I took charge of breaking down views into tasks with full functional descriptions.
Facilitated requirement gathering and handoff.
Provided continuous progress updates.
Resolved any knowledge gaps or impediments.
Quality Assurance
As I had a good understanding of the product space, I played a user acceptance role to ensure we release working software to production.
Design consistency was an important quality metric because if the end product looks wonky, users would not feel comfortable trusting the data.
Context
AdType noticed their customers not being able to provide data they have because of complex software.
Many just stick to the tool they purchased years ago unaware of newer and simpler alternatives.
The goal is to provide a high-level overview of client business data, including offline metrics. Most importantly, it helps companies get more insight from what they already have.
Design process
Discovery
Working on such data and marketing concept heavy product was a bit of a challenge for me but design thinking always shows the way. To understand the context and what we’re building, I:
Gathered requirements from senior stakeholders
Documented findings in one place to create a knowledge base
Facilitated ideation workshops
Created a list of feature requirements
Research
Because I had not designed such a high-complexity data visualisation tool before, there were many things to figure out.
I did competitor research to understand how they do data visualisation to learn that we could lead the way with a clear and understandable story from the data. Explain it a bit.
Understanding metrics was crucial to tell the right story in each report.
I iterated one feature at a time to shorten the feedback loop and accelerate our understanding of the product.
Design
The design goal was to make it easy to see how a large part of a business is doing at a glance.
Colours were used sparingly to show crucially important information that stands out from normal operations.
Implement & Test
I created detailed tickets describing all the features and how they worked and had recurring sync’s with engineers.
Design acceptance was sometimes tough to enforce because an not everyone saw a few pixel offset here and there as an issue to involve developers.
Challenges
Who is the user?
As the development of the tools had only started a few months before I joined, no data was available to understand who would be using the tool.
The assumption was that the main customer base would be Senior people in Marketing, Sales, Management and our team, of course.
Understanding underlying concepts
I am not a marketing professional but I joined a team of many highly knowledgeable ones. This meant that when I was introduced to new requirements, I asked people to explain what it meant and how it worked.
Over time marketing speak stuck and the exposure to concepts raised my baseline understanding.
Challenging old ways of doing
The primary challenge was to change user habits by introducing a flexible digital tool to users who were used to Excel spreadsheets. The slowest adopters were people in management roles.
Facilitating design thinking
The first version of the product was built with little to no design oversight. It worked but it led to inconsistency in colours, layouts, button sizes and general confusion on how to get around.
People were used to handing down Google documents and hand-drawn paper sketches which often led to more confusion. I facilitated several discovery workshops that led to better communication and more shared product knowledge.
Amount of information per screen
Combining data from tens of spreadsheets and other data sources in diagrams, data tables, fitting that into a single view can get complicated. But users made that a requirement to see a full picture.
Product
Based on historical and projected future revenue data users can track business overall performance.
Project future revenue
Users can see the potential revenue the business can earn going on the same trajectory and, by adjusting different attributes, businesses can plan their marketing activities, focusing on the areas with the biggest possible ROI.
Packed with data
The initial challenge of Growth Modeller was to understand what is necessary to be visualized. There are many data points that need to be included for the report to tell the story right. The chart includes 6 different customer types in different times of their life cycle.
Find the most valuable customers
Given that you have acted on the information available, how do you know that you will meet the companies revenue goals this year? This is where the Trend Spotter comes into play.
Data Control
This is the place where you can see how relevant is the data within your reports. This place would show when was the last time online and offline data sources were synced and if any issues need to be addressed.
Growth Modeller
Users can create custom projections by adjusting different metrics like:
Amount of new customers entering the sales funnel
Average Order Value for new customers
Revenue gained by existing customers
Average Order Value of Existing Customers
The most challenging part of this report was visualizing all the necessary data points and metrics in an easy to understand way while still be able to modify different attributes.
You can also switch to Sales Growth which would only include data from sales made online and offline.
Product Report
Depending on the products sold, we can determine customer buying patterns and product profitability.
This helps with understanding which products sell best at what time of the year to better plan and experiment with discounts.
The report also helps to manage inventory by telling when a surplus is needed by anticipating an increase in sales.
For future iterations, it will be possible to select products, select a marketing channel, select users to market to and start a campaign from this screen.
This report can be viewed in pre-set time dimensions or can be set to show custom time frames.
Prospects Database
See customer demographics and use precision tools to start a campaign.
There is a view for each of the databases but the only difference between them are the title and numbers displayed.
You can see how much movement there has been within the database with indicators of positive and negative statuses. The change is visualized as well as explained in detail in the table below.
Since GDPR it is important how it affects your ability to market.
Using the map below shows you the location and the density of people in the database which can be used for marketing efforts in the real world using Display advertising.
Trend Spotter
By explaining that other user types might benefit from this report, I was able to include more explanations about the data and metrics.
This report gives you a detailed insight into business performance and informs the user if revenue targets can be reached based on the current trend.
Widgets at the top visualize key metrics as if the Average Order Value has increased or decreased compared to previous periods.
Variance Report offers a detailed explanation of the metrics mentioned above and offers actionable insights and an explanation of what it means.
Variance report analysis is what you might think. A simpler explanation of the metrics mentioned above. The most valuable explanation here is the indicator that tells you if the revenue goal that was set will be achieved by the end of the year.
Variance report breakdown is there to visualize Variance report analysis, filling in any confusion you might have until now.
The main takeaway from this report is that you will know if your business will reach the end-of-the-year revenue target or if you need to make some adjustments to your marketing plan.
Customer View
We were able to determine how likely each customer was to make another purchase or not make one at all
Here you can find all of a customer’s purchasing history, location history and customer status to better understand their value for the company.
Each customer is given a score that determines their value to the company based on engagement, purchases and other metrics. This means that you could easily identify people who have bought this certain product a few times but not this month, for example.
P.E.C. Database
For precise marketing efforts, each customer database needs to be healthy.
Since the EU’s GDPR law, the importance of understanding which customers you can market to and which ones you should leave alone has become very important, given the possible issues that can come from ignoring this law.
Prospects - are people who have not interacted with your company in any way ex. bought e-mail lists
Enquirers - are people who have interacted with your company by signing up for an e-mail list, filling out a brochure with their contact information or leaving an empty shopping cart (to name a few)
Customers - as you might have guessed, are people who have purchased something from either your online or offline store
This view provides an overview of all three of these databases (yes, you have to separate them for more precise reporting) and sees in what condition they are.
On top, we have the analysis of all entries in the database. This includes duplicates, and people you can and cannot market to. Below that you have people to whom you can market sorted by their source and the ability to create a custom campaign with the included Campaign Builder.
You can see the fluctuations within all databases by month. Each metric in the chart represents all 6 customer types that make up a customer’s life cycle - starting as a new customer and ending as not purchasing anything for 3 years.
You can also see the movement between databases which helps you understand where people are dropping off, how well are they converting between databases and how much money movement between databases (customer states) costs. The cost is an approximation based on many different variables and put together by a very smart algorithm.
Having an overview of all three databases is useful for marketing purposes. If you want to know if you can achieve the end-of-year revenue target, this helps understand if you have enough people in the database that you can market to.
You can also dig deeper into each database where you will find similar information about each of the databases.
Final thoughts
I’ve always been very interested in projects dealing with complex data because you can learn so much.
Not only the complex ways that you can use browser cookies and aggregate data from many different sources to get a very detailed and precise view of your customers and their interests but also the challenge of getting familiar with the different ways to visualize data and constraints you have to work around to make the data tell a story.