How Maggy London uses Shopify Sidekick to power six brands with a 4-person ecom team

Maggy London is a 46-year-old family-owned fashion house that designs dresses for the moments that matter. Founded by Larry Lefkowitz, the company has grown into a multi-brand portfolio spanning six labels—Maggy London, Donna Morgan, London Times, Muse, The Good Journey, and Luxely. Today, the brands are sold through wholesale partners, including Macy's, Nordstrom, Bloomingdale's, Stitch Fix, Belk, Kohl’s, and JCPenney.

As the company invests in direct-to-consumer (DTC) ecommerce, President Sara Bako and her four-person ecommerce team have made Shopify’s AI assistant, Sidekick, an indispensable part of their operations. It helps them analyze performance, audit operations, and make strategic decisions across all six brands.

With Sidekick, Maggy London’s ecommerce team:

• Used Sidekick 21 out of 30 days—near-daily adoption across the entire 4-person team
• Audited and streamlined 199 product collections across six brands
• Detected a major bot attack before any other system flagged it
• Built a data-driven Q3 buy road map that informed the wholesale team’s purchasing decisions
• Created automated Shopify Flows to dynamically tag trending products based on weekly sales
• Reduced weekly reporting time by over 80%, from 3–4 hours to just 20–30 minutes.

The challenge: A legacy wholesale brand ready to own its DTC story

For 46 years, Maggy London built its business through wholesale. With partners like Macy's and Nordstrom accounting for roughly 90% of revenue, the company's direct-to-consumer channel was secondary. When the pandemic hit, and demand for career dresses dropped, the team made the difficult decision to pull back on DTC investment to keep the core wholesale business healthy.

As the business recovered, the company was able refocus on the DTC business. Sara joined Maggy London in April 2022, during the post-pandemic rebuild phase, and is now approaching her four-year anniversary as President of the London Times, Muse, and Direct-To-Consumer Business. She recognized early that DTC wasn’t just another revenue channel. It was the only place the brand could fully own its narrative.

Wholesale partners sell dresses, but they can’t communicate a 46-year legacy. They can’t speak to the legacy of the brand, the story behind the style, or the intention behind a new brand like Muse. Only Maggy London’s own site can do that.

The challenge was scale. Sara’s ecommerce team—just four people supporting six distinct brands—had to operate at a level most companies handle with much larger departments. Across the business, design, wholesale, product development, and factory partners stay aligned through a deeply integrated Airtable ecosystem, with Airpower powering key Shopify and ecommerce workflows. The infrastructure is strong.

But on the DTC side, execution still came down to Sara and her four direct reports. Site operations, merchandising, analytics, and marketing all ran through that same lean team, making focus and prioritization critical.

"Shopify is an excellent platform for organizations like ours because it provides intuitive systems and products that do not require an in-house developer," Sara said. "But we needed something that could help us think, not just execute."

That something was Sidekick.

The solution: Sidekick as an AI team member

From curiosity to command

Sara began using Sidekick in October, when DTC was added to her scope and she started working more directly in the Shopify admin. With no technical background, she approached Sidekick the way she would any new colleague—by asking questions.

"I started asking basic things, like pulling information about our Black Friday business or details about our current theme so I could build a proposal for the team," Sara said. "I treated it like taking a class. I'd frame my prompts as solving a problem or validating a pattern I was seeing in the business."

Sara trained Sidekick to deliver weekly business performance summaries, pulling year-over-year analytics into a single snapshot that she could review and then drill into for deeper analysis. She started bouncing ideas off Sidekick before presenting them to her team.

"I view Sidekick almost like an additional team member because I'm able to maintain running conversations and keep historical context," Sara said. "I'll ask it a question, get the answer, and then go three layers deeper based on what I see."

Multi-brand intelligence

Sidekick proved especially valuable in helping Sara’s ecommerce team generate insights that informed the entire company—not just DTC operations. 

Sara quickly began applying Sidekick across a range of operational and strategic decisions. Examples include:

The 199-collection audit. When Sara suspected that Maggy London had accumulated too many product collections across its six brands, she asked Sidekick to audit them. Sidekick analyzed all 199 collections, provided information on collection structure and best practices, and generated a CSV file the team could use to systematically clean up underperforming pages. That cleanup is still underway and directly affects how customers discover products on the site.

Cross-brand customer behavior. Sara used Sidekick to analyze purchasing patterns across all six brands and uncovered a key insight: customers weren't brand-loyal. They shopped across Maggy London, Donna Morgan, London Times, and other labels interchangeably. This discovery reshaped how the e-commerce team thought about cross-brand merchandising and marketing.

Q3 buy road map. One of the most strategic applications was building a buying road map for the upcoming season. Sara asked Sidekick to pull historical data on styles, recommend unit quantities based on the financial plan, and identify key hero styles. This analysis informed the final buy plan and helped the product development team.

Wholesale recut validation. In many cases, the ecom team pulls historical data first and sends it to the wholesale team so that when they see a new collection, key styles online have already been taken into account. This has allowed opportunities for the wholesale team to test styles that the ecom team feels confident about placing. When the wholesale team planned to recommit to styles from the prior year, Sara's team used Sidekick to double-check total units sold and size-selling data before finalizing those decisions.

New vs. returning customer analysis. Sara regularly uses Sidekick to compare year-over-year new and returning customer behavior, including revenue, orders, and AOV. She also tracks which styles are most popular with new customers versus returning ones, giving the team a clear picture of what drives acquisition versus retention.

Security and site health

Sidekick also proved its value in an area no one expected: security.

In December, Sidekick was the first system to flag a major bot attack on Maggy London's storefront. Sara brought the issue to COO Jon Lefkowitz, who worked with Shopify support to implement new bot-protection software. Without Sidekick's early detection, the attack could have gone unnoticed for much longer.

Sara's team also uses Sidekick to investigate site infrastructure and uncover optimization opportunities that would normally require a dedicated analytics team or expensive third-party tools. Some of the questions Sara’s team now answers with Sidekick include:

Search intelligence. Sara used Sidekick to analyze the top search terms customers were entering on the site over a three-month period, then cross-referenced that with search-driven traffic and conversion data. The result was a clear picture of what customers are looking for versus what Maggy London is presenting on the site. This gap now directly informs merchandising and collection strategy.

Landing page optimization. The team analyzed which landing pages received the most sessions over specific periods, identifying which entry points drove the most engagement. Combined with data on the highest-converting day of the week, this tells the ecom team where to focus marketing efforts.

Automated merchandising with Shopify Flow. Using Sidekick, Sara’s team created a Shopify Flow that identifies the top 20 best-selling products each week, automatically tags them as "trending," and removes the tag after seven days. Maggy London's site now always surfaces what's selling—without anyone on the team manually updating collections or merchandising pages.

Review-to-conversion analysis. Sara’s team used Sidekick to investigate whether product reviews were driving conversions. By comparing products with reviews against those without, she was able to make data-based decisions about where to invest in review generation.

Return pattern analysis. When certain styles showed higher-than-expected return rates, Sara used Sidekick to flag the issue at the product level. To understand the why, the team pulled detailed return reasons directly from Loop, giving the design team clear feedback on fit, fabric, and sizing issues that don’t show up in high-level reporting.

Faire marketplace tracking. Sara also used Sidekick to track views and clicks on Maggy London’s Faire-hosted wholesale page, giving the team visibility into marketplace performance beyond the Shopify storefront.

Preparing for AI discovery. Sara’s team also used Sidekick to locate and update URL redirects to set up an LLMs.txt file, preparing Maggy London’s storefront for discovery by AI-powered shopping agents and search tools. Most brands haven’t even considered this step yet.

The results: From near-daily adoption to company-wide intelligence

Near-daily adoption across the team

The numbers show how deeply Sidekick is embedded in Maggy London’s day-to-day operations. In a typical month, Sara’s team uses it on 21 out of 30 days. About 75% of those interactions are analytics-driven—pulling sales data, comparing year-over-year performance, and analyzing product trends down to specific styles and colors. The rest support site operations, merchandising workflows, and security monitoring.

Sara reported measurable impact across the board:

• Time saved. Sidekick frees up at least a full day of work each week.
• Faster decision-making. Analysis that once took days—or multiple back-and-forths—now happens in minutes.
• Cost efficiency. The team avoided hiring an additional analyst or investing in separate analytics tools.
• Reporting speed. Reporting time has improved by roughly 10x (1000%). What used to take days of prep for buy meetings now takes just a few hours, with full buy plans completed in the same window.

Faster decisions, fewer dependencies

With a team of four people managing six brands, Sidekick has effectively eliminated the need for a dedicated data analyst. The ecom team can pull performance reports, build customer segments, audit collections, validate wholesale decisions, and analyze merchandising trends—all without waiting for another department or hiring additional headcount.

Sidekick has also changed the speed of decision-making. Instead of compiling data requests and waiting for responses, Sara gets answers in real time and can follow inquiry threads immediately.

A weekly business review that might have taken hours of manual data pulling now takes minutes, freeing the team to focus on strategy rather than reporting. When Sara needed a new merchandising app, Sidekick recommended Sorted Merchandiser along with two alternatives, and the team used those recommendations as their starting point for evaluation.

Company-wide AI adoption

The most significant result may be what happened beyond the ecom team. Sara's adoption of Sidekick coincided with a company-wide AI mandate from Lefkowitz, who gathered all 60 employees about a year ago and made it clear: AI is here, and like the internet, everyone needs to learn how to use it. 

Rather than issuing a mandate and leaving teams to figure it out on their own, he built the infrastructure to support it. The company created an AI champions program with a dedicated Slack channel and a second company-wide channel where employees share how they’re using AI. What began as monthly sharing sessions soon evolved into a weekly Friday speaker series where anyone can demo an AI workflow they’ve built.

"What we learned is that people need to see it in action to be able to use it," Sara said. "The demos are what unlock adoption."

All four ecommerce team members now use Sidekick daily or multiple times per week. One team member, Chandrel, cross-references Sidekick outputs with ChatGPT and Gemini when evaluating best practices. The broader organization—from design to factory coordination—is also sharing AI techniques across departments.

"Sidekick is the starting point because it knows our business," Sara said. "We cross-reference with other AI tools, but Sidekick has the context of our store, our products, our customers. That's what makes it different."

Sara's own enthusiasm has become a force multiplier. "I am Sidekick's biggest fan and cheerleader," she said. "It's crazy not to use it. It can do so much to streamline your workflow."

What's next: AI-powered styling and modernized storefront

Maggy London's next strategic priority is transforming the customer shopping experience through AI. Sara envisions a future where customers don't scroll through endless pages of dresses but instead interact with the site the way they'd talk to a personal stylist.

"I want a customer to be able to say, 'I need a dress for my daughter's wedding' or 'I'm curvy, what would look good on me?' and get personalized recommendations," Sara said. "That's where we're headed."

For Sara, Sidekick has already proven what's possible when a small team has the right AI tools. The question now is how far they can push it.

"We started with basic questions. Now we're building buying road maps and catching security threats. I can't imagine going back to how we worked before."