Converting eCommerce Store Traffic into Shoppers
Using Contextual Trust as the Model for Conversions
One of the biggest satisfaction of retail merchants, is in seeing prospects convert into a sale. This is a baseline measure of success in the global retail domain.
To achieve this, merchants and retailers have leveraged their understanding of human psychology in determining what fuels purchase intent of shoppers.
I’ll be walking you through some of these principles currently being used.
Classical Conditioning — Priming
Think about an ad where a person uses a skin care product and then ends up with beautiful skin, that is what we call priming or classical conditioning.
The aim here is to get consumers to associate this product with a desirable feeling or outcome (having a beautiful skin)— which subsequently should drive consumers to purchase this product.
In classical conditioning a conditioned stimulus is associated with an unrelated unconditioned stimulus to produce a behavioural response — called a conditioned response.
Operant Conditioning — Positive or Negative Reinforcement
Operant conditioning (based off of B.F. Skinner’s theory on human learning behavior) refers to changes in behavior as a result of experiences that occur after a certain behaviour.
This type conditioning is least known because behavior is controlled, or conditioned by reinforcement or punishment. Since Pavlov’s groundbreaking discovery on being able to condition animals to give a particular response, numerous studies have shown that such conditioning is equally effective on humans.
Recently behavioral conditioning has become a powerful tool for brands and marketers looking to generate awareness and loyalty.
Operant conditioning attempts to modify behavior through the use of positive and negative reinforcements. Through it, an individual makes an association between a particular behaviour and its outcome
Marketers leverage heavily on the use of rewards to reinforce a desired behaviour — conversion. Examples of this include the use of promotional sales (discounts, perks, add-ons etc) to drive product purchase.
Mere Exposure Effect — Ads
This effect is a psychological phenomenon where people tend to develop a preference for things merely because they are familiar with them. It is sometimes known as the familiarity principle.
The more you see or hear something, the more you like it — this is the mere exposure effect
Advertisers rely heavily on this when selling a product or service: billboards, banners, radio and TV ads, as well as digital advertising such as social media ads, shopping engine marketing, search engine marketing.
The goal of ad placement within view of a target audience is to drive the liking of a product, service or content among this audience. The continued exposure to this ad should lead to a higher probable interest in the product.
Reciprocity — Helping
Reciprocity or the rule of reciprocity is a social norm where if someone does something for you, you then feel obligated to return the favour.
Usually when a marketer offers a target audience relevant insights, it is expected that this audience will reciprocate the gesture through a purchase.
The ad industry has taken advantage of these techniques to ensure that traffic harvested converts to clickthroughs for a product, service or content. This industry has undergone changes in various forms due to tech disruption: with traditional advertising occupying a shrinking but relevant niche for brands looking to target offline audiences.
Digital marketing remains ever relevant as audience targeting, placement, budgets can be refined on-demand — all geared towards higher conversion and customer acquisition rates at lower costs to brands.
But the question is how can you effectively measure the success of an ad?
The effectiveness of a digital marketing campaign is measured as a ratio of people who took the desired action compared to the total number of people who saw the ad (impression). This is called the click-through rate (CTR).
Currently the average ad CTR is 1.91% — which means that for every 50 ad impressions, only one desired action is performed.
Now for performant ad types, Google Search ad placement has a CTR of 3.17% (3 clicks out of every 100 impressions) with the display network at an average of 0.46% (23 clicks in every 500 impressions).
These metrics serve as a guide for merchants looking to drive traffic or perform a specific action on their stores.
Contextual Trust Leads to Higher Conversion Rates
Trust (in psychology) is believing that the person who is trusted will do what is expected. It starts within a family and grows to other areas including our social network. Trust evolves through our interactions which ultimately develops into contextual trust.
In getting higher conversion rates, contextual trust as a model uses algorithms that converts store traffic at 10x industry CTS rates.
Let’s break this down:
Hethie may trust Jessie (because she is a fantastic gourmet cook, but not a makeup artist) to recommend groceries for an orzo salad but not on which cosmetics to use.
Here’s another: there’s a social event coming up and you’re looking to grab a fancy wear for this. A friend’s recommendation whose taste you trust in fashion will most likely get you to purchase, compared to clicking on an ad online for dinner wear.
Contextual trust implies that recommendations from people we trust has a higher outcome (clicks to store, conversions etc) compared to suggestions based on an ad or digital campaign.
Just because you trust your friend’s recommendation in clothing, doesn’t mean that you’d trust her recommendations on whether to get an iPhone or a Samsung, places to eat, or travel bags to buy.
That’s contextual trust! Got it?
So how will this work on your online store? Rendezvous enables store visitors to get contextually relevant recommendations by generating and sharing catalogs from your web store with their trust network across all messaging apps.
Earlier, I mentioned that because trust is contextual, users get to share store catalogs with people whose recommendations they trust. Now this is where the model for higher conversions occur:
• Users are more likely to purchase an item recommended from their trust network.
• By sharing these catalogs, store products get a higher reach and visibility, within a network which finds direct value from it. A store visitor will likely share catalogs with their trust network made up of 3–5 persons.
Rendezvous which enables this is built on the Rendezvous Graph — a patented technology which leverages artificial intelligence and machine learning to offer highly relevant recommendations to users based on what they need.
In 2019, the click-through rate for catalogs shared and recommended using Rendezvous was 21.34% — 1 out of 5 catalog impressions yielded a click to store with a purchase intent.
Now the industry average is 1.91% which means that Rendezvous beat this metric by more than 10x. If you’re a merchant on Shopify, you can position your products for discovery and increase sales with Rendezvous today.
In our next post, I’ll walk you through how you can enhance conversational discovery and get more conversions on your store using Rendezvous.
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