How do you calculate your key data metrics in Salespath?

Engagement and Coverage

We call engagement and coverage a score, because we are using an algorithm to calculate these numbers. The goal is to use the data to identify two fixable issues:

• Engagement- Whether a salesperson is missing cars when they really should be there. This would be something we want to address with the individual salesperson. Our calculation determines whether an individual sales associate is consistently using the Salespath tablet to deliver presentations to customers.
• Coverage- This is whether we have staffing issues and simply do not have enough salespeople during working hours. This is something we would want to address with management as far as staffing.

The bottom line is that when operators stay focused on keeping both of these scores in check, sales go up.

Attribution

First, we need to look at every single POS transaction that came through the pay lanes and see if a salesperson was connected to that transaction. We call this process attribution. If we see that the logged in salesperson gave a presentation either 5 minutes before, or 5 minutes after that particular POS transaction, we attribute that transaction with the salesperson. If a car comes in after that 5 minute window, we would consider that a "missed car". We do this because it is normal for a salesperson to step away to help with something, to use the restroom, or to help a customer. However, if cars are consistently missed outside of that 5 minute window it is an issue that results in reduced sales.

Engagement Score

Engagement Score is based on how many POS transactions the individual salesperson was attributed to compared with how many retail cars there were while they were working. Again, this is based on whether that sales associate is consistently using the Salespath tablet to deliver presentations to customers. This is a calculated number because if we simply went by how many presentations were launched, the system would be easy to beat as sales associates could launch presentations even while they are not selling. We also often see presentation sessions launched thinking the approaching customer is retail, when in fact it is a member visit. For this reason we cannot simply go by the number of presentations launched divided by the number of retail cars.

We begin by looking at the salesperson's first and last presentation of the day. For example, let's say we have a salesperson named John and we see a presentation given at 8:00AM, and another at 4:00PM, we assume John was working during those hours.

So, he has his first presentation at 8:00AM. If he floats away to talk to his co-worker and misses the car that comes in at 8:04AM, we will give him the benefit of the doubt and attribute him to that transaction since it is within 5 minutes. However, if he continues to stay away, and another car comes at 8:06AM, we will not attribute that transaction to him and it will be considered a "missed car" which is the responsibility of the salesperson. Therefore, at that moment, he has a 66% Engagement Score because he was attributed to the first 2 cars, but shows up as missed for the third (e.g. we consider him engaged for 2 of 3 cars, 2/3=66%).

Coverage Score

Let's continue with our above example and say that John now continues to be away from the pay area (and therefore not giving presentations). When the car comes at 8:11AM we no longer consider this a "missed car", but instead consider it an "unattended car", which will now count towards coverage score. The reason is that it is rare for a salesperson to be on the clock, but remain away for longer than 10 minutes without anyone knowing. Usually this happens because the manager has asked him or her to help with something else. All of the cars that come after that are counted as unattended until John returns and begins giving presentations again. At that point the clock starts over and the transactions are being attributed to John.

Member Count

The member count you see in your member report is updated once per day and is from the previous night when we look at your POS and pull an active member report. It is not updated live during the day for new signups.

To understand the exact member count, it is important to understand Grace Period. (DRB builds this in, but other POS companies do not, so we build it in on our side.) In all subscription businesses, there are regular attempts to charge cards that are no longer valid. For example, an expiration date might have hit, the customer might have gotten a new card, or the card might simply be over the limit. In all of these cases the POS software will attempt to charge that card each night and will do so for several days. Grace period is typically set somewhere around 4-7 days and says that we will not remove this customer as an active member until the specified amount of days has passed and all attempts have failed. Only then will we remove them as an active member. This is because very often the card is updated at some point by the issuer and the once declined credit card will now work.

Without a grace period, that member is immediately removed from the active member list on night one, and only to be added back on day two or three when the card is updated. This results in regular chatter in the active member count. With grace period it removes that chatter and gives you a truer sense of active members.

$/Car

$/Car represents the average amount spent by customers during retail transactions. It excludes all new signup transactions, providing a clear view of how much your customer base spends on each visit. To calculate this metric, the system adds up all retail transaction amounts (excluding any new signups) and divides that total by the number of cars (minus new signups). Therefore, the formula would be: $/Car = Total Retail $ ÷ (Total Cars − New Signups).

For example, If 100 cars visited your wash, 10 were new signups, and the remaining 90 retail customers spent a total of $2,700, then: $/Car = $2,700 ÷ 90 = $30.00.

Churn & Churn Rate

We calculate churn by again referencing your active member list from the POS. Each night when we pull your member list we compare it to the night before and see which members are no longer active (taking into consideration grace period mentioned above). The ones that are no longer listed are considered churned. 

For monthly churn rate, we add up that daily churn number for the previous 30 days and divide it by the total member count 30 days ago. By definition, churn rate does not include signups during the 30-day period. (Churn rate can also be calculated annually, but in car washing we typically always use monthly. Annual churn rate is your average monthly churn rate multiplied by 12.)

Please Note: One of the fundamental elements of increasing sales is making sure we are presenting to every single customer. Salespath uses presentation data from the tablet as well as POS transactional data to intelligently determine whether we are missing any opportunities. 

Questions about your Salespath data? Contact us at support@rinsed.co!