When you think about a typical working day, which customer inquiries do you enjoy the most?Â
I am most pleased about a request for a new Product Advisor: a customer wants another Product Advisor for their new product series and sends me a briefing with the desired conversation!
Which trbo feature do you particularly like implementing, and why?
I particularly like working with the In-Page Advisor from trbo Advise. This is a full-screen advisor that integrates seamlessly into the online store and helps customers find the right products. With this feature, I can create a very clear and visual product advice.
The Advisor offers me many implementation options, different types of questions and options. This allows me to implement almost all of my customers’ ideas and requests, usually even in different variants, and therefore find the best possible variant of the product advisor.
I can then even use the collected user data from the Advisor for further use cases during the customer journey.
Do you have an example for us and can you explain the function in more detail?Â
For example, we can use information that we have collected via the Product Advisor for personalized product recommendations in trbo Personalize.
For example, if a customer’s store has many different product categories, i.e. a broad product portfolio, it is particularly important to display suitable products or product categories to store visitors. Once a visitor is on the website and has completed a consultation, we already know a few things about this visitor:
- which product category was searched for?
- which products were recommended?
- other details that the visitor selected during the conversation
We can then use this information/data to personalize product recommendations even beyond the consultation:
A visitor who completed a consultation searched for printer paper for CANON printers and was recommended suitable products. This user can now be shown other suitable products via trbo Personalize product recommendations. A user who has not completed the consultation would, for example, see classic product recommendations that are not based on their preferences, but on other logics such as “is often bought together”. By linking trbo Advise and trbo Personalize, the website can be further personalized.
At which point in the user journey is the implementation of the feature best suited and why?
This implementation is best suited to the respective category page, but the user must have started a consultation once so that the product recommendations can be personalized in this form. If a user finishes a product consultation and then returns to the product category page, they can be shown personalized products that have either already been recommended to them or have the appropriate attributes, i.e. are based on their preferences.
An online retailer would like to implement the feature on their website. What advice would you give him before implementation?
On the one hand, I would advise placing the product advisors prominently, e.g. on the homepage, on category pages or on a specially created landing page. This gives more users the opportunity to start a consultation and then receive personalized product recommendations.
On the other hand, the customer should consider for which product categories this implementation makes the most sense and creates the greatest benefit. This implementation makes particular sense for product categories in which various additional products are offered.
What advantages and opportunities does this measure offer?
The clearest advantage is that the store can be further personalized based on this data. Especially for stores with many different product categories, it can be very helpful if users see products tailored directly to them. This makes them feel immediately picked up. Bestsellers or products that are not performing so well can also be pushed more.
For which industries is the use particularly worthwhile? Can you give us a few results or a particularly successful use case?
This feature is particularly useful in sectors where many different products and categories are sold. Thanks to the personalized website, users do not feel overwhelmed by the enormous variety of products.
But the topic can also be worthwhile for stores with a smaller variety of products. For example, information already obtained could be used to directly display a desired or suitable color or size in a product recommendation if a user has already provided this information in a consultation.
Is the option an all-time classic or do you think its impact has been underestimated so far?
With the inclusion of Advise in trbo’s product portfolio, this option is still fairly new. The impact is currently still underestimated and can still significantly increase store performance.
trbo’s product portfolio consists of the 4 products Personalize, Advise, Chat and Bundle. Personalize offers the perfect user experience with the right content at the right time. Advise improves sales and customer experience with our product advisor. Chat can automate 50% of your customer inquiries with our AI chatbot and Bundle offers perfect product bundles and shop-the-look offers for every user. Especially in combination with each other, the products can unfold their full potential.