With the first quarter recently in the books and Q2 well underway, most companies have their collective eye on an uncertain economy and an inconsistent consumer. But for some companies, it’s beginning to look a lot like the holidays.
Count Balsam Brands among them. The upscale eCommerce and D2C holiday decor retailer has to fit what would be a whole year’s worth of revenue for any other company into Q4. And with the runaway growth of artificial intelligence (AI), that means shaping up its data profile so it can continue a digital transformation that has been accelerated since the recent arrival of Chief Technology Officer France Roy.
Roy, who came to Balsam from InBev, where he managed 400 data scientists and engineers, said he enjoys connecting technology and AI to revenue growth, even if it needs to be packed into the holiday season.
“I love the growth that came through my experience at InBev as well as the challenge of digitally transforming a company,” he told PYMNTS recently. “That’s what drew me to Balsam. You have the digital transformation that needs to happen in an amazing company that is establishing itself as a luxury brand in the U.S. To take a joyful experience for everyone and use data to unlock the value of this business is an exciting opportunity.”
Lest you think the word “growth” doesn’t fit at a company that has staked its claim to the upscale artificial tree market, consider some data.
According to the American Christmas Tree Association, approximately 21.6 million real trees and 12.9 million artificial trees were purchased by U.S. households during the Christmas season of 2023 at an average price of $46 and $78 accordingly. Artificial trees are not the only holiday décor and accessories the company makes and sells directly or through retailers like Nordstrom’s, but it is their core product.
When he came on board five months ago, Roy found data scattered across various systems, lacking consistent organization.
To modernize Balsam’s data infrastructure, Roy partnered with SoundCommerce to integrate consistent, compliant data models in Snowflake, enabling the company to avoid time-consuming data transformation and achieve faster time-to-value.
But he’s not stopping there.
With its data house in order, Balsam Brands is turning to AI and large language models to enable business users to query data using natural language. The aim is to empower non-technical teams with real-time compliant data access to inform decisions during the critical holiday sales period. AI will also power new website capabilities to personalize the shopping experience based on a customer’s intent and past purchases.
Over the longer term, granular customer data will allow Balsam to define key segments, such as high-value customers, new buyers and repeat purchasers at risk of churning, and determine the optimal channels and messaging to engage them.
“With all these new capabilities, we’re going to be able to track and optimize in a very robust way for different customer segments, which is something we don’t do today,” Roy said.
While Roy sees immense potential for AI in retail, he acknowledges that many tools are still nascent. He anticipates a rapid acceleration in the space over the next couple of years and aims to keep Balsam Brands on the cutting edge by leveraging new AI capabilities as they emerge. Roy wants his marketing colleagues to gain a unified view of digital marketing data, combining conversions, attribution, spend and activity.
At the same time, eCommerce teams will have consolidated shopper engagement data from web, cart, email and SMS interactions for customer profiling, segmentation and campaign automation.
Ultimately, data and AI are all about growth for Balsam Brands as it seeks to expand its footprint in existing markets and new geographies. Roy sees data as key to gaining a deeper understanding of customer segments and regional preferences to drive growth in both mature and emerging parts of the business.
“At Balsam Brands, we know the importance of using trustworthy data to drive world-class experiences for customers and better company performance,” Roy said. “We’re building future-proof data infrastructure for machine learning, advanced analytics and data activation. The goal is to make the data and the tools easy and effective for every business stakeholder across our company.”
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