Google vs in-store analytics

Di seguito vi riporto un interessante articolo di Ronny Max apparso nella sua newsletter, dove è ben evidenziato come le possibilità di analisi del comportamento del consumatore da parte del retailer siano esageratamente sbilanciate verso l’online e molto poco verso il negozio fisico. In pratica: Google analytics vs in-store analytics.

If you want to compare online and offline metrics, this is the most critical email you should read this year because the comparison is often misleading. In the online world, time-based metrics generate signals about the user’s intent. The same holds for physical stores.

And yet, here are nuances in time-based metrics

1) Dwell Time
Google wants to show their users the BEST results for any query.
Google measures a web page’s quality with backlinks, but engagement with Dwell Time, Bounce Rate, and Time on Page.

• Dwell Time: the time between “clicking” on a search result and returning to Google’s search result page (SERPs).
• Bounce Rate: the percentage of visitors that visited only one page on the website. It doesn’t matter if they stuck around for 2 seconds or 2 hours. The visit is still a “bounce.”
• Time on Page: The time a visitor spends on a specific page before “clicking out” to any other page on the website, Google results, or anywhere.
But wait, is Dwell Time good for “shopping queries” when you are comparing between products? We don’t know for sure, but Google is smart 🙂 Google is about queries and clicks. YouTube is about watching videos.
While Google cares about giving users the best result for their query to click, YouTube cares about users staying on the video site.

Here’s how YouTube evaluates content

2) Watch Time
YouTube is that it wants to show its users the best video at any given moment. To evaluate the best video, YouTube measures how the users interact with videos.
The metrics revolve around video engagement.
• Audience Retention: the percentage of your video that people watched. It is an excellent indicator of video quality. It is also a metric that’s difficult to game.
• Total Watch Time: YouTube #1 most important metric. The total amount of time that people have spent watching your video over its lifetime. The higher the number, the better.
• Engagement Signals: YouTube wants to see users actively engage with the video through likes, comments, shares, subscribe, and adding a video to the playlist.

Again a time-based metric plays a crucial role in capturing intent

Total Watch Time signals how long users stayed on YouTube because of that video.
3) Engage Time
What retailers want in physical stores? If your answer is sales, think again.
Store sales are an outcome. And many factors influence an outcome.
If you want to follow the footsteps of Google, your objective will be to quantify in-store customer engagement. That’s the job of a time-based metric. In customer engagement, you have three metrics: Visibility, Attention, and Engagement. These are big topics.
Today, I’d to focus on how long a shopper interacts with a product.
Engage Time signals the “intent to buy.”

In other words, the simplest way to measure customer engagement is to capture how long a person stays in a particular location. With advanced technologies, you can measure customer engagement in seconds.
You can also capture the product’s Optimal Engage Time.

In other words, the time between “no engagement” and “needs help” signals that a shopper has a valid interest in the product.
For example, if you want to know how many clothing items are best for a premium display, you can check the time shoppers stand in front of the display. (By the way, more items are not always better).
Another example, if you want to know if the frozen foods packaging stands out, you can check the time shoppers stand in front of the freezers.
(By the way, too much time is not always a good sign because it may indicate confusion).
Time-based metrics will help you to dig deeper into customer behaviors.

Misurare il coinvolgimento del cliente in-store

Google analytics vs in-store analytics: Google riesce a misurare la qualità di una pagina ma anche il livello di coinvolgimento dell’utente che vi interagisce ed è questo l’anello mancante delle analisi che in genere si compiono nei negozi fisici. Dalle considerazioni di Ronny Max emerge quanto sia importante riuscire a misurare il coinvolgimento del cliente, magari rilevando quanto tempo rimane fermo in un determinato luogo, o quanto ci mette prima di chiedere informazioni su un prodotto.