Title | GIFT BOT |
Brand | LEGO |
Product/Service | LEGO |
Category |
E01. Social Business & Commerce |
Entrant
|
EDELMAN London, UNITED KINGDOM
|
Idea Creation
|
EDELMAN London, UNITED KINGDOM
|
PR
|
EDELMAN London, UNITED KINGDOM
|
Production
|
EDELMAN London, UNITED KINGDOM
|
Credits
Lars Silberbauer |
LEGO |
Senior Director, Social Media & YouTube |
James Poulter |
LEGO |
Head of Emerging Platforms and Partnerships |
Eleni Karamalegkou |
LEGO |
Director, Social Media & YouTube |
Ksenia Barton |
LEGO |
Social Media Strategist |
Sheila Yau |
LEGO |
Performance Marketing Manager |
Genelle Holton |
LEGO |
Digital Marketing Manager |
Myles Cameron |
Edelman |
Head of Creative Technology |
Stu Hallybone |
Edelman |
Group Creative Director |
Matthew Cannington |
Edelman |
Director, Head of Social |
Nick Robinson |
Edelman |
Senior Social Strategist |
Dan Douglas |
Edelman |
Content Strategist |
Adam Lee |
Edelman |
Technical Developer |
Georgia Watts |
Edelman |
Senior Project Manager |
Background
Buying gifts for children can be daunting. The amount of choice is often overwhelming and finding a present the child will really love is a tough task!
In a recent survey, 84% of respondents did gift research online, but over a quarter said this was just as stressful as going into the shops.
For LEGO, this daunting purchasing decision is a problem. From shop.LEGO.com through to their retail partners (e.g. Amazon), customers are met with an enormous selection of LEGO sets that can leave them feeling confused and unable to make a purchase.
LEGO wanted a solution that would assist customers in navigating this confusing landscape, helping them find the perfect gift that the child would actually love. They needed an interactive solution that would help LEGO discover who the customer was buying for and provide relevant suggestions based on their likes and interests.
Describe the strategy
LEGO’s review of gifting across the peak period discovered that customers were overloaded with choice, and feared failing to give a gift that the child liked. We needed a solution that helped address both issues and was as individual as the customers.
We wanted to target parents and gift givers who were looking to buy presents. We identified multiple mindsets that would help us divide this audience and create custom journeys to ensure routes were relevant.
Facebook was the most relevant platform for the parents and gift givers that we wanted to reach.
We recognized that not every customer would want the same journey within our chatbot. Some would like to get a gift suggestion as quickly as possible, whilst others preferred a deeper dive into the LEGO world. We started with our audience mindsets and created multiple entry points and versions of Ralph which would address the customer’s requirements.
Describe the execution
LEGO Gift Bot's success depended on the Chat Bot's Digital Design. The look, feel and tone of the bot needed to emanate the LEGO's brand feeling, whilst delivering a premium digital service which was actually helpful to consumers in their purchasing, rather than a mere novelty.
To make every gift suggestion perfect, we developed questions around price range, age, personality and interests. This meant the mammoth task of recategorizing LEGO sets, assigning them to new categories that were specifically designed around our interests and personalities. These categories provided relevant suggestions that suited customer’s price point, child’s age, interests, and personalities.
A custom API that provided real time, localized stock updates from store.LEGO.com, and gave customers a unique free shipping code and gift. A single tap completed the purchase through store.LEGO.com.
Development = three weeks
Targeted Facebook promotion to customers with relevant direct messaging
UK, US, Canada, Germany, France and Poland
List the results
• The chatbot reached over 2.69 million people.
• There were 1.2 million post engagements around the bot, achieving an engagement rate of over 45%.
• Ralph had conversations with over 50 Thousand potential new customers.
• The bot was responsible for driving 25% of all in-season online sales, providing a 6x return on ad spend within certain markets.
In a direct comparison study with other conversion-based ad formats (such as carousels, Canvas and collections), the bot drove a 8.4x higher conversion rate and a cost per purchase that was comparatively 65% lower.
• Ralph was an experiment to simplify the purchasing funnel for low affinity customers, guiding them through a complicated landscape in an easy to follow manner. Our comparative study proved Ralph’s ROI was far beyond that of other conversion formats
• Ralph has been hired to help LEGO customers on a full-time basis!