Between April 2014 and April 2015 (13 months), growth for online only retailers was 20.2%, while for multichannel retailers it was 8.1%.
Online pure play retailers have lead the way in recent growth terms, adopting and executing key initiatives as launched by Google.
A fantastic example aiding this growth is Google’s 2015 launch of audiences for shopping which enabled advertisers to target users based on behaviours, purchase patterns, on-site activity, their place in the purchase funnel and overall value to their business.
More information on how to create a Shopping Remarketing List is here.
Further development was announced this week as Google launched Customer Match for Shopping providing an invaluable addition to the shopping arsenal allowing the savvy marketer to execute more targeted campaigns to re-engage with businesses’ most loyal purchasers.
What is Customer Match for Shopping?
Customer Match itself is nothing new – it already exists for Search, Gmail, and YouTube (as I’m sure you’re aware).
It allows the uploading of a list of email addresses, which can be matched to signed-in users on Google in a secure and privacy-safe way.
What can you do with this data?
In practical terms, the shopping initiative allows you through your own existing customer email address data, to take your offline and online signals, and re-engage your loyal shoppers as they shop on Google.
You might typically focus on treating differently or bidding more / less aggressively on areas like:
• High-value audiences
• Previous purchasers
• Rewards members
• Newsletter subscribers
• Local in-store shoppers
But it is also equally important to focus on;
• Low value purchasers
• Repeat purchasers
• Seasonal purchasers, e.g. a rain coat for wimbledon!
• Purchasers of designer products this season
• Purchases around events at this point last year – Birthdays / Mothers day / Valentines / Christmas
The more you categorise your data, the more effectively you can target – this is key, both in the traditional customer match sense of building more lookalike users or those that behave and shop in a similar manner. With customer match for shopping it should effect the exact bid or strategy changes to the most targeted of audiences, this will put you in the pole position to maximise your returns.
How it works
According to Archana Kannan, Product Manager for Google Shopping:
“Customer Match can be used to increase the visibility of your brand and products to your highest value customers as they search.
Say you’re a retailer that specialises in sporting goods and you have a rewards program for die-hard baseball fans. Since it’s baseball season you have a segment of customers who are likely thinking to make a purchase soon. By using Customer Match, you can increase your bids for this segment. So the next time a fan searches for gear, you can meet him or her with the right product at the right time.”
We have been running this in beta for lots of clients here at Croud, and can now happily share the initial results for one of our top retailers:
• We increased our bids for specific CRM audiences to reach them as they were in market for our client’s products
• Conversion Rate was +114% better than the average Conversion Rate across the Shopping account (4.5% versus a 2.1% average)
• We segmented people who were particularly interested in designer brands from the rest of the email database which is already leading to a 20% uplift in sales
We hope that you’re as excited as us to start! You can learn more about our best practice for shopping here, and sign up for the feature here. If you want to learn more about how we could run customer match for you, don’t hesitate to get in touch!