Interactive Powers · Simulation model

Phygital Store Simulator

A full day in a home appliance and hardware store. Customers browse, look around and buy; some ask for help in the aisle, others for a brand demonstration, and others for a card transaction or a credit application at the counter. X, the share of visits that go to customer service and credit, is an input; Z, the share of those transactions completed successfully, is the business figure, and the customer rating scores service across the whole store. It compares the conventional store with adding Video Kiosks, digital endcaps and QR codes served by VCCaaS agents. A Video Kiosk is not self-service: there is a person on the other side, serving by video.

Day type
X · Go to customer service and credit
12%
Scenario
Store
09:00
Interaction minutes by where service happens · click to jump to that time

Floor staff

Brand experts

Counter

VCCaaS agents

Staff and screens

Each scenario is set separately. By default, scenarios 2 and 3 have fewer floor staff and brand experts, because the digital endcaps and Video Kiosks serve by video, and the same counter as Scenario 1. Try removing counter positions and look at Z in “What changes in the store” and at the costs.

VCCaaS in scenarios 2 and 3
Stores
6
Experts
2
Cust. service
1
Scenario on screen · up to the clock time
Sc 3

+ Video QR

In the store0
Waiting0
With staff0
On video0
Z · Service and credit completed
–
Customer rating
–
Leave unserved
0
Average wait
–

Interaction minutes

What changes in the store

Interactions and outcomes

Green: more served, fewer lost or shorter waits than in Scenario 1

See detail: shared or dedicated VCCaaS

Shared versus dedicated

Same store, same day and same customers. “Occupancy”: average of the VCCaaS agents during opening hours.

Economics · scenarios 1, 2 and 3

Same day and same customers in all three scenarios. The store pays for in-person and remote service, digital endcaps, Video Kiosks and QR totems. Sales are not estimated: the outcome of service is measured with Z, the customer service and credit transactions completed successfully, and with the customer rating.

Store parameters

They apply to all three scenarios. Moving a value recalculates the day and the animation continues from the same time. Values with a source have published backing; the rest are working assumptions: adjust them with the client's data before showing any amount.

Visits and day

Visit journey

Waiting and patience

Video and QR

Customer rating

Costs

How the model is built · sources and assumptions

A day in the store

  • Customers arrive according to the day type. Low, medium or high, each with its hourly curve: high is a weekend or a payday, with more load at midday and in the late afternoon. Each visit includes at most one assisted interaction; the rest only browse and buy.
  • Aisle info. The customer looks for someone from the floor staff. They only see staff in their own aisle or the ones next to it, and free staff move around the store. If they see no one free before their patience runs out, they leave without the information.
  • Floor staff also restock. Part of their time goes to restocking and tidying, and meanwhile they do not serve customers.
  • Brand demonstration. Each expert stays at their own display. If their brand has no customers they stand idle, even if the next display has people waiting.
  • Customer service and credit: X and Z. X% of visits go to the counter for a card, a payment, loyalty or a credit application, taking a ticket and queuing. Anyone who sees a wait above their threshold leaves. Z is the share of those transactions completed successfully; a credit approved by video counts once the signature is also done.
  • The customer rating. It scores service across the whole store: a 10 if the customer is served on time, points off for each extra minute and a low score if they leave unserved. It is a model index, not a survey.

What changes in each scenario

  • 1 · Conventional. In-person staff only. The endcaps are passive screens: advertising, no interaction.
  • 2 · + Video Kiosks. Some customers go straight to the digital endcap in their aisle or to a Video Kiosk for the demonstration or their transaction. The rest look for staff first and switch to the screen if they find no one or see a queue. On the other side, a VCCaaS agent by video.
  • 3 · + Video QR. In addition, QR totems at the counter, in the brand area and at the head of the aisles, in that order as more are added: the customer continues on their phone, in front of the product or while they keep shopping. QR is only available where there is a totem.
  • Each scenario has its own staffing. Floor staff, experts, counter and screens are set separately in “Staff and screens”, to see how much staff is needed with video.
  • There are people in the VCCaaS. Two groups: product and brand experts, and customer service and credit. Dedicated to this store or shared with the chain, whose stores are simulated the same way, each with its own volume.
  • Customers who need their transaction use the screen. If the counter queue is not moving, those who preferred a person also move to a free Video Kiosk, as long as the transaction can be done by video.
  • In-person service does not disappear. When a counter position becomes free, it serves whoever has waited longest, in the queue or at a Video Kiosk waiting for an agent. And some credits approved by video go through the counter at the end, for signature or delivery.
  • Service cost: CX Gap rates. Each in-person interaction costs 13.50 USD and each one with a VCCaaS agent, 7.16 USD; kiosks, endcaps and totems are paid monthly. In the parameters you can switch to cost per position.

Sources and assumptions

Out of scope: checkouts, stock-outs, after-sales, home delivery and sales. The outcome of service is measured with Z and the customer rating, not in revenue.

The model assumes that the VCCaaS agent can check the store's catalog and stock and process cards and credit in the same systems as the counter. Without that integration, video service is limited to general information.

Simulation model with working assumptions. It is meant for comparing scenarios with each other, not as a forecast. Interactive Powers · interactivepowers.com