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Northern Trail Outfitters (NTO) was unable to process coupon codes for several days, when caused customers to complain about their experience. NTO would like to apologies by offering an upgraded coupon to help improve customer satisfaction
What should NTO do to automate the process of finding its affected customers?
Suggested Answer: A
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30 comments · newest first
NE
Nelida
11 months ago
Surprised they didn’t have this automated already!
NO
Norah
11 months ago
Using Einstein scores sounds fancy, but is it reliable?
NO
Noble
12 months ago
But what if some customers used coupons outside that range?
CY
Cyndy
12 months ago
Definitely agree, that’s the easiest way!
LU
Luis
12 months ago
I think filtering by date range makes sense.
KA
Kanisha
1 year ago
I feel like using Einstein engagement scores might be overkill for just finding affected customers. Filtering by date seems simpler.
AN
Andra
1 year ago
Querying the data sounds like a solid approach, but I wonder if it would be too complex for this situation.
TR
Tresa
1 year ago
I remember a similar question where we had to identify users based on engagement scores. That might be useful here too.
MI
Mitsue
1 year ago
I think filtering the data by date range could work, but I'm not sure if it captures all affected customers.
DA
Dacia
1 year ago
This looks like a tricky question, but I think I can figure it out. The key is to carefully analyze the device paths in the output and determine the sequence they would be used to boot the system.
RE
Regenia
1 year ago
This one seems straightforward. I'm pretty sure handlebar Templates are defined in the cc_hk_UserInterface extension, so I'll go with option C.
VI
Viva
1 year ago
Ah, I see. The key is that biometric data is permanently tied to the individual, so it can't be replaced like a password or ID card. That makes sense.
GL
Glory
1 year ago
Ah, I remember this from the lecture! Network-Based IDPS is designed to monitor and analyze traffic across an entire network, so it can detect and respond to threats that span multiple computers. That's gotta be the answer. Nice, I feel good about this one.
JO
Johnson
1 year ago
I'm a bit stumped on this one. Is it FANZ? That doesn't sound right, but I can't recall the actual Arista feature for microbursting diagnosis. Guess I'll have to make an educated guess on this.
SH
Shenika
1 year ago
C definitely seems like the correct answer. Anything involving 'Einstein' in a business context is just trying too hard, if you ask me.
AV
Avery
1 year ago
Haha, Einstein engagement scores? What is this, a sci-fi movie? I'd stick with the good old date range query if I were NTO.
ES
Estrella
1 year ago
User 3
DO
Donette
1 year ago
User 2
CA
Carey
1 year ago
User 1
LA
Laurel
1 year ago
A date range filter seems like the most straightforward approach. It'll help NTO pinpoint the right customers without any fancy analytics.
GA
Garry
1 year ago
Automating the process will definitely save time and improve customer satisfaction.
LE
Leonora
1 year ago
Maybe NTO can also consider sending out a mass email to inform customers about the upgraded coupon.
NE
Nell
1 year ago
Implementing a date range filter is a good idea. It'll make it easier to identify affected customers.
RO
Ronny
1 year ago
Option C looks like the way to go. Querying the data using a specific date range should help identify the affected customers efficiently.
YO
Yolando
1 year ago
Once we have the list of affected customers, we can then reach out to them with the upgraded coupon as a gesture of goodwill.
FE
Fernanda
1 year ago
I agree, that way we can quickly identify who was impacted by the coupon code issue.
LE
Leoma
1 year ago
Option C sounds like a good idea. We can filter the data by date to find the affected customers.
MA
Marta
2 years ago
I think querying the data using a specific date range parameter would be more efficient in finding the affected users.
BE
Bernardine
2 years ago
I agree with Vanda. Using a specific date range will help narrow down the affected customers.
VA
Vanda
2 years ago
I think NTO should filter the data based on a specific date range.