I am just over a week into my &pizza internship, and I am having a blast. Without further ado, let’s jump right in!
Did you know that you could have gotten a $3 pie from &pizza just for catching a typo in one of President Trump’s recent tweets? &pizza’s latest innovative promotion invited customers to text them with typos and did just that, all thanks to the Federal Reserve “cuting” interest rates and someone who is allegedly “very bad under pressure” being a “chocker.”
My work for &pizza involves carrying out performative marketing analytics, which relates to determining the effectiveness of different advertisement campaigns and evaluating sales. So far, I have been using a combination of Google BigQuery, a SQL-based cloud database, and Domo, an online data visualization software. Think of Google BigQuery as your local grocery store, containing tons of items organized in a series of categorized aisles (called tables) that each contain different items in various specified quantities (specified in columns). SQL lets you select a subset of items of your choice and put them in your shopping cart (called querying). Domo is where you make a nice, presentable, and consumable dinner out of all the items that you have purchased (called visualization).
So far, I have been exploring data from BigQuery in Domo relating to key performance metrics (KPMs) detailing traceable sales, customer loyalty, and customer value.
Traceable sales are digital sales: sales from &pizza’s application program interface (API). These are the sales for which &pizza has the best data since the customer directly makes the transaction through &pizza, something that is not true when a customer uses a third-party service like UberEats, Grubhub, or Doordash to order &pizza. In those instances, UberEats, Grubhub, or Doordash collect information about the customer, but that information is not shared in full with &pizza.
Known sales relates to the sales for which &pizza is aware of who the customer is. If the sale is digital through &pizza’s systems, &pizza definitively knows who the customer is because the customer is using an account—meaning, the customer has self-identified and agreed to the collection of information. If the sale is not digital, it gets much dicier. When a sale is not digital, &pizza typically does not know who the customer is: for example, &pizza has no idea whether the customer is trying &pizza for the first time ever or for the fifth time this week.
Knowing the customer behind a sale is valuable. It lets &pizza understand the customer’s loyalty, the success of their promotional campaigns with that customer, and their success in customer retention and acquisition. You may have noticed that companies like Chipotle, Potbelly, Dunkin, and Starbucks, among others, offer you rewards if you use their mobile app, while other companies like Safeway offer customers discounts if they use their “Club Card.” In effect, companies are offering their customers discounts for better data. They use this data to more effectively and accurately market to their customers and, hopefully, to increase average customer value: that is, the total amount of money that a customer will spend, on average, at the company during a specified period of time.
Businesses shape many of their initiatives about increasing customer value, and, conventionally speaking, there are three primary ways to do so:
1. Increase frequency: get people to visit the restaurant more often. For example, offer customers who might not have come recently a promotion to try to get them in the door. Offer a customer who hasn’t come in three weeks a half-priced pie. Offer another customer who comes in only at lunch a free craft soda with the purchase of any pie during dinner hours.
2. Increase spending per visit: get people to spend more at the restaurant per visit. For example, give a customer a free craft soda with the purchase of a pie so he or she can try it out and hopefully come back for more. Offer a buy-one-get-one-free promotion. Offer a new line of items, or potentially even raise prices.
3. Open more stores: have more places for people to give you money. Leverage costs of development, advertising, distribution across more stores.
The Domo dashboard I am in the process of creating will update these KPMs autonomously through a series of queries configured to run periodically at specified intervals.
Outside of data analysis, what was the highlight of the week? Meeting new people and getting to see the whole of the business. It is amazing to see how all of the moving parts work together: whether that is seeing one team strategizing for upcoming promotions, another keeping all of the technology running smoothly, and another outlining the emergency plan for the coronavirus. Plus, the free pizza last Friday in the office didn’t hurt… &pizza makes really good pizza pies :).
With continued excitement and curiosity after much exploration and dashboard creation, please be sure to stay tuned for next week!
P.S. I want to start a fun, potentially weekly feature that I am going to call the stat of the week. Usually, it will just be something that I found interesting in the statistics world; odds are it won’t be &pizza related because I have to keep those stats internal, but nonetheless we can still have some fun. Here’s a fun stat I discovered this week during my commute to &pizza: did you know that the Rosslyn Metro station is accessed by an escalator that is 194 feet long according to Matt Johnson of Greater Greater Washington? I did some calculations, and, using the maximum height of a given step of seven inches and the minimum depth of 11 inches according to Century Group, this equates to approximately 164 steps if the escalator were stationary. Looking down from the top certainly makes you think about holding onto that dirty, but stability-ensuring moving escalator railing.