December 21, 2011
I’m going to let you in on a secret. At RunColo we send out a monthly e-blast where upcoming races can advertise their event. I’ve gotten good, really good at being able to pick out which races will have the most click rates. You might think its name recognition or the description of the event, yes those things help, but the number one factor is the logo design. Does the logo capture the reader’s attention, if it does that generates a click. If you create a flyer or a postcard for your race and place it in a local running store the same logic applies, your race flyer will be sitting there competing with all of the other races, will the customer pick up your flyer?
It’s common for races to cut cost when creating a race logo. They hire a friend to design a logo or they simply grab a photo off the Internet or even worse from Clip Art. Spend a hundred or two hundred dollars and get a logo that is professionally done. The ROI is positive.
As they say on Madison Avenue, “you never get a second chance to make a first impression.” When I see a weak logo, my first thought is that if they don’t care about their logo how much are they going to care about their race? Yes, I am generalizing, but that’s what people do.
Another pet peeve of mine is a lot of races that benefit children will have a contest where the children get a chance to design a logo and the winner is used for marketing and for the race t-shirt. I’m not a fan of cute; I’m a fan of professionalism. Everyone loves art work from their kids or kids that they know, but I’m not interested in having a crayon drawn logo on a race shirt and I can assure you that those shirts go straight to Goodwill. If it’s one of my own kids, I make an exception.
Most races look at the race t-shirt as an obligation. They buy the cheapest cotton t-shirt they can find and slap a generic logo on there. Look at the race t-shirt as future advertising, advertising for next year’s race. Why spend $4-$6 on a shirt that no one wants, instead put some effort into the logo so that people will wear that shirt and your race will be exposed to future runners.
If you’re a race director get that permit and then start working on the logo, it’s money well spent.
December 6, 2011
Anyone who has run a race has incurred the agony of showing up on race morning and getting in line to pick up your bib and chip and wondering why the pre-registration lines are so unevenly distributed. You’re in a line with 20 other runners and you look over at the S-Z table and notice the volunteer running the table on their iPhone with not a runner in sight. Why does this always happen?
Before becoming a full time race timer, I was a business analyst and one thing that I loathe are bottlenecks. You don’t need a black belt in Six Sigma to reduce congestion on race day but you will have to do some basic math.
One simple rule of data analysis is to look at the data before you make a decision. However a lot of race directors make the mistake of breaking out the registration tables by the alphabet and not by how the runners who have registered fall within the alphabet.
Here is the alpha breakout from the 2000 census, first letter of the last name:
If a race director broke out the pre-registration table into halves, the above chart shows the participant distribution. Using data from the 2000 census this would create a scenario where 63% of the race day participants are going to the A-M table and the other 37% are going to the N-Z table.
What we recommend is analyzing your pre-registration information and assigning the breakouts according to the actual percentages. Utilizing the census data we would look at the breakout and find the point that allows us to most evenly distribute the participants over two tables. The larger the race the more tables and breaks you’ll want to create.
A lot of people with the last name beginning in M! Thus by creating alpha breaks of A-L and M-Z, we were able to distribute the breakout to 52%/48%, which will help alleviate bottlenecks on race day and create a smoother race day experience for the racers and volunteers.
This is a basic example, but carry this logic forward if you’re breaking your pre-registration tables into thirds, fourths, etc. Don’t rely on the census date, look at your data before assigning the alpha breakouts.