J.Lo may say “Love Don’t Cost a Thing”, but Americans are planning to spend $136.57 on Valentine’s Day anyway.
When I chanced upon the results of NRF’s Valentine’s Day Spending Survey I knew it was the perfect material for this week’s post. Data from a reliable source that’s actually relevant and interesting? Ah, be still my geeky heart.
In today’s post, I talk through the thought process in coming up with an infographic like the one I made above.
What are the data?
The first thing I did was read through NRF’s whole press release. I emphasize whole because NRF chose to chart some data, while only talking through others.
e.g., They made a chart for planned gift recipients:
But only mentioned the planned budgets in text:
This year’s survey found consumers plan to spend an average $85.21 on their significant other/spouse, $26.59 on other family members such as children or parents, $6.56 on children’s classmates/teachers, $6.51 on friends, $4.27 on co-workers, and $4.44 on pets.
It’s easy to miss some data just because there weren’t any visualizations for them.
Since I didn’t want to miss out–after all, the juicy stories might be the ones in hiding–I made sure to read through the whole thing, keeping a tab of what data were available.
Here’s my tab, in bold are what I ended up using:
- Planned Valentine’s Day spending for the past 10 years.
- Average planned spending in 2007, 2016, and 2017.
- Percentage planning to celebrate the holiday in 2007 vs 2017.
- Average planned spend per recipient.
- Planned Valentine’s Day gift recipients.
- Planned gift purchases for Valentine’s Day in $.
- The mismatch of giving vs receiving experience gifts.
- Planned gift purchases for Valentine’s Day by percentage.
- Where consumers plan to shop for these gifts.
What’s the story?
The next step was to figure out what story to tell with this data.
I found the data interesting, but I’m admittedly biased towards numbers. I had to find a reason for people to want to read the data.
So, I made the story as relatable as possible.
I’m an average guy/girl. I’m spending Valentine’s Day with someone really special in my life, and I want to make sure they know it. I’m going to spend my hard-earned cash on them!
But I don’t know how much to spend.
Am I already overspending? Or am I a being cheapskate?
How much is everybody else spending?
I crafted the story in terms of what an average person might Google and get the above data as a result.
From there, it was a matter of deciding which of the data could expound on the story.
Below was my chosen storyline:
How much is Valentine’s Day going to cost me?
Does it always cost this much?
What should I buy?
How much should I budget?
Okay, but only because he/she’s my significant other. What about everyone else?
How can I save?
I was planning to stick to three main points, but I added that last item because I wanted to remind people that they could always just opt out of the holiday. I wanted the story to have a twist at the end.
What tool to use?
Initially I was planning to bust out some complex Excel charts, or maybe even Power BI because I was playing around with it last week.
I even found out that a similar data set was featured on #MakeoverMonday, so a bunch of people were posting all these pretty visualizations made with Tableau. Yay, inspiration!
But then I re-read my storyline. And thought again of my target audience.
Was there any value in using fancy visualizations?
Begrudgingly, the answer was no. I wanted my audience to relate to the data, not be alienated by it. And in order to do that being simple is key.
For example, I thought it’d be cool to give a year-on-year comparison of the average spending on Valentine’s Day:
This is the kind of thing that excites product owners and sales managers. But the average Joe or Jane? Nah, prolly not.
I also considered re-interpreting NRF’s Planned Gift Purchases chart:
But I think people are more concerned about what other people are buying, rather than the relative amounts. So I highlighted that: I used icons to represent the most popular gifts, and downgraded the chart values to supplementary numbers.
In the end, we have an infographic made 100% in Canva. No fancy visualizations. Hmph.
It’s like I planned for a novel but walked away with a short story.
Because its for Valentine’s Day and because its one of my favorite colors, I opted for pink.
It turned out to be a little bright though, so I used the slightly darker shade #E2AE9D instead.
As for fonts, I kept the fashion theme going by applying the fashion retail font pairing recommended by Canva. That is, Bebas Neue with Montserrat.
Coincidentally, Bebas with the brown background looks like a popular chocolate brand.
Overall the most difficult part was finding the story. It was a struggle trying to come up with questions people want answered versus what answers I already had with me through the data.
An easy way out would have been to take NRF’s summary and run away with it:
Valentine’s Day continues to be a popular gift-giving occasion even if consumers are being more frugal this year.–Matthew Shay, NRF President and CEO
But I chose not to. Instead I took the hard path of trying to be “relatable”. sigh.
The aesthetics were fun. I love pink, so choosing a main color was a no-brainer. The accent colors and fonts were more deliberate choices, but made easy thanks to guides.
I’ve shared what I could out of this infographic, and I’d love to hear what you think. Any type of feedback would be appreciated.