Learn to make product data actionable in a way that delights the end-customer and protects their privacy.
Nikole Wintermeier | Nov 01, 2021
Learn to make product data actionable in a way that delights the end-customer and protects their privacy.
Are you facing so much data on your webshop, you don’t know what to do with it?
Are you struggling to leverage this data for personalization?
You’re not alone.
In Adobe’s report on Customer Analytics, only 9% of respondents said they had an integrated digital analytics solution for personalization.
ECommerce analytics may seem complex and vast. Plus, brands that lead the race are 141% more likely to have analysts and data scientists on board.
But making sense out of data doesn’t always need a statistician or data scientist. Sure, it can help.
But speaking from a company that has our own data-savvy people on board, we know it’s enough to understand terms like product intelligence. And how to leverage your product analytics to make the most of your data.
Product intelligence is how your brand can create a more meaningful customer experience (CX) on your webshop, optimize product discovery journeys, and – the cherry on top?
Make data actionable for personalization across more than one channel. This article will help you navigate product intelligence by:
Product intelligence is the process of gathering and analyzing your product data and making it actionable on your webshop or omnichannel.
Where product data tells half the story of your customers, product intelligence fills the gap and makes your analytics actionable.
Much like customer intelligence, your product analytics answers the who, what, where, and how of your products.
And based on these data points, product intelligence answers the why.
This means taking a product-centric approach to your data. Now, you may be thinking: But isn’t a product-centric approach outdated?
To help you understand, let’s go back in time for a second.
Back before advertising leveraged consumer psychology, products were sold based on their attributes. For example, this Accutron watch ad from 1966 highlights every technical aspect of the watch.
Selling product attributes as benefits wasn’t always obvious. Luckily, brands have now evolved to start putting the customer at the center of their marketing campaigns.
Which is why today, products are mostly sold on how they benefit the lives of the customer. Even super utilitarian products are sold with the customer’s ‘clothes’ and ‘wallet’ in mind (see: IKEA’s product description).
Apple watches are a holistic product – improving health, fitness, and livelihoods, rather than simply telling time.
This shift from product-centric marketing to customer-centric marketing was quite the revolution for retail.
And like all revolutions, it doesn’t stop there.
What we’re already starting to see with the rise of eCommerce (and, ultimately, more people shopping online than ever before), is that marketers are now merging the worlds of product-centric and customer-centric.
Product-centric + customer-centric = Product-driven customer experiences
Since more retailers are shifting their marketing approaches from commerce to content, merging product-centric and customer-centric is crucial.
And it’s an approach that will start in eCommerce. By creating product-driven customer experiences, you can start:
Product intelligence is all of these things combined. It’s what you make out of the data from marketing customer-centric products.
Your eCommerce platform is already gathering and analyzing myriad product data points like clicks, boughts, and product trends. Analyzing how your products perform is part of building out this data-centric architecture.
Once again, your product analytics answer the who, what, where, and how of your product data. Product intelligence, on the other hand, answers the why.
We know why people buy coats in the winter, but why they would choose one over the other is less obvious – understanding data means first making assumptions about it. And then testing, testing, testing, to prove or disprove your assumptions.
Then, something like, ‘Why do people buy coats in the winter’ can be answered with, ‘because it’s cold’. And making this actionable could look like creating an email campaign offering gloves, hats, and coats together.
In short, Product Intelligence gives context to your data so that you can personalize your product messaging and promotions across multiple channels.
“Product personalization brings back several elements that retailers have neglected since the shift from product to customer-centricity. By understanding and properly communicating the characteristics of your products to the right person at the right time, you are catering to both goal-oriented and browning shoppers while reducing choice overload.” - Janelle De Weerd, Head of Growth at Crobox
Apple is a genius example (pun intended) of how product intelligence works. They continuously gather information about how people use their products daily and then use this information to make improvements.
Their models are always innovative. They stay ahead of the industry. And keep customers coming back for more.
But aside from allowing brands to innovate their product offering, product intelligence will also let you stay ahead of the data curve.
It’s no secret that customer data is becoming increasingly more protected with stringent laws like the GDPR in Europe and the ITP (intelligent tracking prevention) creating barriers to gathering data.
Yet, 80% of consumers are more likely to purchase from a company that offers personalized experiences.
In other words, your challenge is twofold:
Product intelligence lets you take on these two challenges head-on. By shifting the focus to your product data, you can actually bring the two worlds of product-centric and customer-centric together online.
For example, Crobox’s Product Recommender will show product recommendations based on the customer’s context, preferences, product popularity in relation to other products, and real-time stock information.
This is all data that’s gathered in-session.
We don’t track individuals across other platforms. We simply see what kind of interactions they had with your webshop’s products, in order to personalize the products they see for up and cross-selling.
Consumers are willing to pay up to 16% more on products and services for a good CX.
So how do you improve the CX by focusing on your product data?
You start by optimizing how you communicate with your customers. Product intelligence lets you personalize how your products are shown, and what messages are used to promote them.
For example, take Product Badging. At Crobox, we define badges as promotions that can be shown on a product through behavioral nudges leveraging Social Proof, Scarcity, or Authority.
Here, machine learning comes into play to auto-optimize the product messages a shopper will see. So if a shopper has recently browsed ‘Bestseller’ products, they are more inclined to see similar Social Proof messages (i.e., ‘Bestseller’, ‘Most Bought’, In ‘High Demand’).
This is product personalization in a nutshell because it:
The more you can tailor your products to the individuals searching for them, the better you can make the overall CX and perception of your brand. In this context, product intelligence will see:
Product Intelligence can also pave the way for continuous product innovation. Understanding why people shop for the products they do will help you drive purchase behavior in the long run.
Because you can start creating products that are more in line with your customer’s preferences – all by tracking their behavior on-site.
Dynamic Messaging leverages product badges, but also notifications, and overlays. These are promotions that leverage AI to show the right message at the right time to the right person.
For example, Crobox helps retailers collect intelligence about what kinds of product USPs appeal to their shoppers.
We can ask, is the USP ‘waterproof’, ‘sustainable’, or ‘lightweight’ more relevant to your customers' shopping behavior?
If it’s ‘waterproof’, your manufacturing and design teams know to create more waterproof products in the future, as this is an attribute more likely to appeal to your shoppers.
Product intelligence can be leveraged from marketing to manufacturing, especially if you can extract and share this data across departments.
Product intelligence helps you see where and when to promote your products. Including how to organize your product taxonomie in line with the shopper’s decision-making framework.
For example, let’s say your message ‘Bestseller’ is performing well for the customer segment ‘mobile-shoppers-coming-from-Instagram’.
You can optimize your mobile taxonomies by including a Bestseller category page. Or, place Bestseller products high on your Instagram page to promote the findability and visibility of products your customers like most.
Check out the ASICS example below for how we elevated the merchandising experience.
Your marketers – digital or otherwise – will be able to leverage product intelligence to plan and optimize campaigns.
For example, knowing that a product has a high abandoned cart rate means you can send retargeting emails to nudge your shoppers back to complete their purchase. Or, knowing when a product is most bought can help you think around a relevant, seasonal campaign.
It’s about looking at product data to:
Product intelligence will also inform your offline channels, like fulfillment (stock) as well as how your floor employees guide sales.
For example, say you’re leveraging a Product Finder on your webshop to help people find the perfect running shoe.
If your online data tells you that the majority of your customers are looking for shoes with more stability, ensure this is visibly promoted in-store in the section where these shoes are found. That way, more of your customers know exactly where to go to find the products they’re looking for.
Alternatively, you can place high-performing product badges on your webshop in-store to draw attention to certain products.
For instance, if you know that sustainability messaging drives click-behavior on-site, try placing these as labels in-store.
The bottom line is that whether you’re a merchandiser, marketer, or in-store staff, there are many ways you can think about leveraging product intelligence.
Let’s take a look at three big product intelligence brands for more inspiration.
Crobox built ASICS’ Shoe Finder, a tool that matches customers with their perfect running shoe by asking them a series of questions.
Braingineers, a neuro-usability company, stepped in to test the usability of the Shoe Finder 1.0. What they found was that more people were missing a ‘Trail running shoe’ option.
With this data, ASICS decided to create a separate category in their taxonomy for ‘Trail Running’ to highlight these shoes and make search and discovery that much easier.
ASICS could also take this product intelligence to their other marketing channels. For example, creating content around trail running to educate their audience via email or social.
RayBans uses product data to understand what attributes appeal to their customers. By allowing you to ‘customize’ their glasses, they can understand what different visiting segments love about their iconic products.
Is it the traditional aviators? The wayfarer style? Do they like them in black, matte, with brown cases?
As the customer makes these choices themselves, the webshop can start understanding:
And with this in mind, RayBans segment their audience by their behavior and then optimize their campaigns.
Getting data on how people make product decisions by letting them choose is a sure-fire way to stay within data protection laws.
That’s because what RayBans is doing is leveraging zero-party data. In other words, customer-approved data that can be used to personalize without infringing on legislation.
Using product intelligence in this way:
It’s a win-win if I ever did see one.
IKEA actually leverages a dynamic message, with their ‘New lower price’ badge. This serves to:
Which are great ways to optimize the product discovery experience. Simply by pointing out the price of the product, IKEA is able to:
Check out more ways to leverage persuasive pricing here.
Product intelligence comes in when behavior is tracked. So if many products with the same message are engaged with (clicks, boughts), then IKEA knows this is something that ‘new lower price’ appeals to their shoppers.
Which means they could take this messaging to optimize their SEO, adding similar price-sensitive terms like ‘affordable’, ‘discount’, or ‘ 50% prices’.
IKEA does indeed position themselves as an affordable brand. But this assumption can be easily tested on-site, by tracking how their customers engage with their products.
In its essence, product intelligence can go from granular to large. Clicks can be turned into KPI uplifts. Which can further foster:
While product intelligence may seem complex, I hope you now believe that even the most non-data-savvy person can start making data actionable across different channels.
Let’s break it down.
Crobox has this great feature called Product Profiles, where you can see all your product data centralized in one place. Because the more digestible your data, the more you can start making it actionable.
Want to learn more? See our platform in action.