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D.R. Truth - ask him anything!

Jon,

You already have a boatload of queries, here's more ;-)

  • How does Qweb (i.e. engagement) differ between mobile and desktop?
    • I assume mobile use will have shorter TOS and less pages viewed, ergo less Qweb. If this is true, does qweb mobile have (or need) it's own tracking?
  • If you separate qweb desktop & mobile, what happens with correlation to sales?
 
...adding another log to the Mobile vs Desktop discussion...

It's easy to guess that desktop usage is strongest for 'top of funnel' use and mobile's strength is the 'bottom of the funnel' (the Dealer's happy place ;-).
  • Is there a way to test this assumption?

This is an especially interesting topic as the pioneers in our space are trying to understand the ROI of a full-tilt "Mobile 1st" mindset. For example, speaking as a dealer decision maker, the output of this study could significantly influence my PPC spending (moving more $ to mobile) and possibly adding more weight to Social ads (as most social use is mobile).

And, this info may cause me to obsess on 'things that make my mobile qweb go higher (e.g. page loading speed, improved UI, etc).

DR Truth = Stop the Guesswork!
 
Bump to the Top!
@jon.berna 's Hope you find some time to drop more jaw-dropping "Truths" on us :) Your insights can be game changers!


...adding another log to the Mobile vs Desktop discussion...

It's easy to guess that desktop usage is strongest for 'top of funnel' use and mobile's strength is the 'bottom of the funnel' (the Dealer's happy place ;-).
  • Is there a way to test this assumption?

This is an especially interesting topic as the pioneers in our space are trying to understand the ROI of a full-tilt "Mobile 1st" mindset. For example, speaking as a dealer decision maker, the output of this study could significantly influence my PPC spending (moving more $ to mobile) and possibly adding more weight to Social ads (as most social use is mobile).

And, this info may cause me to obsess on 'things that make my mobile qweb go higher (e.g. page loading speed, improved UI, etc).

DR Truth = Stop the Guesswork!
 
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Jon,
Plz explore qweb (dealer web site engagement) and sales activity.
  1. Is there a relationship between qweb score (i.e. shopper engagement) and future sales activity?
  2. Are there events that trigger higher correlation (i.e. a store's qweb increases past some threshold & sales follow x days later), or, do sales trends follow qweb trends week over week/ MoM?

Have you done a sales -vs- qweb study on stores who's qweb has made a significant increase/decrease?
Example:
If a store has a qscore of X and commits to engagement over lead gen, what is the likelyhood they'll they see a lift in sales?
If there is a correlation, is there a time lag (i.e. qscore rises in week one of january, sales rise X weeks later)
Great stuff!


I see where you want to take this, however there is some complexity when evaluating user level stats at the day and month level. When you track by day the user stats get cloudy. This is because this is an advanced user segmentation. So when we track this at the day level you get users that for the period you are evaluating that met the 3 conditions (time on site > 400 secs, > 7 pageviews, and > 4 sessions). This is hard to explain so let me try:

Say on Monday 5 users hit the criteria
On Tuesday 6 users hit the criteria. However 2 of these users also met the criteria on Monday and visited the site again

If you look at this by day you see 5 on Monday and 6 on Tuesday
If you look at this by month you see a total of 9

For this reason it is really best to look at Qweb by month as the session criteria of 4 or more you really need to give it time to accrue. Looking at the lagging effect of highly engaged users on sales makes sense but would require a different approach.

There is a correlation between Qweb and Sales. I will post that next.
 
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So I pulled some reports and evaluated the correlation between Qweb and Sales. I pulled data on 6 stores as this has to be done one at a time and is kind of a PITA, the results were getting clear so I figured it would be enough to tell the story. Basically Qweb Used goes up so does used car sales (58% is a strong association)

Qweb New = Qweb criteria + they looked at a new VDP
Qweb Used = Qweb criteria + they looked at a used VDP


Qweb-to-Sales.png


I would also use this an efficiency metric from marketing engagement to sales. The higher the correlation the smoother / more consistent the process. More random = high variability. High variability means the store is not managing to leading indicators. Each month is bringing a major course correction from one extreme to the next. This can show up for a number of reasons, here are some common examples we see.

  1. Used car supply goes up sales go up, then used car supply falls sales falls, process repeats
  2. GM compensation based on net profit influenced by previous month overall bonus payouts. Dealership does well / bonus payout goes up. Next month GM doesn't try as hard (as they are hit with large increase in expense) results go down, process repeats. SPIFS cause this as well.
  3. Every other month direct mail/TV/SEM fill in the blank here.
  4. Dealership does well, dealership hires more, dealership converts worse and sells less, people leave, process repeats
If you think about your store just remember variation is bad. If you want to get nuts on reducing variation check out Six Sigma (the DMAIC model is your friend)

Here is the detailed data on the that orange Ford Anomaly. This essentially means the results are completely random, this is a completely possible result, but definitely an outlier.

Ford-Anomaly.png
 
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Fascinating!
So if USED units are sticky(er) to car shoppers (than new), is there an unseen benefit to a new car store that has a strong used car presence? Do you have evidence where a dealer significantly increased its # of used units? And if so, what happened to qweb?

I see a lot off stores that have made heavy investments in buffing up their CPO unit counts and then pricing them very low as a mechanism to sell more new cars. Some stores exclude these units from the strict 60 out policies as they are drivers of traffic. This technique is not new, however the execution in marketing and website setup requires some consideration to maximize results.

Also, this is not to switch the customer or play games. The idea is to create choice and educate.
 
Last edited:
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...adding another log to the Mobile vs Desktop discussion...

It's easy to guess that desktop usage is strongest for 'top of funnel' use and mobile's strength is the 'bottom of the funnel' (the Dealer's happy place ;-).
  • Is there a way to test this assumption?

This is an especially interesting topic as the pioneers in our space are trying to understand the ROI of a full-tilt "Mobile 1st" mindset. For example, speaking as a dealer decision maker, the output of this study could significantly influence my PPC spending (moving more $ to mobile) and possibly adding more weight to Social ads (as most social use is mobile).

And, this info may cause me to obsess on 'things that make my mobile qweb go higher (e.g. page loading speed, improved UI, etc).

DR Truth = Stop the Guesswork!

My exp/gut tells me desktop = more dedicated searching (brain is focused on collecting data) including jumping from car to car, brand to brand. Mobile = researching what you already saw on desktop and less focused on data collection more focused on validation. Validation to me means engaging in content to confirm the current best vehicle(s) in consideration. The process repeats from data collection to validation until a tipping point or trigger.

IMHO I don't think I would place a strategy on mobile vs desktop. I always try to find value. What is under priced relative to it's value for me and the dealership's strengths. Lately I have been having the conversation below with ad agencies and large groups.

To me the under valued market right now is leveraging the dealership's customer data in Google customer match, Facebook's custom audiences and programmatic. This is due to the barrier of entry in terms of awareness and technology gap.

Simple logic: If it's hard for my competition to do it they won't because they are lazy. If I am smart and work harder I will do the things they won't and win because of it. They won't do what I did until the pain of not doing it hurts more than doing what I did. By then I am on to the next thing...

Efficiency-Quads.png
 
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Done for tonight. I mentioned Six Sigma in a prior post. I was professionally trained by the gentlemen that wrote this book back in my online education days in 2006 and it changed the way I looked at everything. As I travel all over and discuss analytics it is clear to me many people have missed out on an essential understanding of statistics and how to evaluate a process.

For example, ask your colleagues or vendors some of the following (in order of difficulty). If they can't answer them immediately why are they consulting you and/or making decisions on your data???

  1. What's the actual formula for ROI? (they say it every day so it should be easy)
  2. What's the difference between a correlation and a conversion?
  3. Why would you use a histogram chart?
  4. Whats the difference between normal and special cause variation?