How Bacca Bucci, India's Fast-Growing D2C Footwear Brand, Drove 15X ROI Through Netcore's Agentic Marketing Platform

Founded in Delhi in 2013, Bacca Bucci has grown into one of India’s leading D2C footwear and accessories brands, built around the idea of giving trend-conscious customers design-led style without a premium price tag. The brand has served over 45 lakh customers to date, ships more than 4,000 orders a day, across a catalog of roughly 3,700 SKUs spanning sneakers, boots, athleisure, belts, and wallets.

Industry Context

India’s footwear market is large and expanding fast, projected to grow from $17.9 Bn in 2024 to $45.5 Bn by 2032, but it remains split between mass-market players competing on price and established global brands competing on premium positioning. Homegrown, digitally-native brands like Bacca Bucci compete in the crowded middle, where sale events such as BOGO promotions are a key growth lever but also a high-risk one: a poorly targeted blast can just as easily erode margins and annoy customers as it can drive revenue.

For Bacca Bucci, the question heading into its June sale wasn’t whether to run a promotion, but how to make sure it reached the customers actually likely to convert.

For Bacca Bucci’s CRM team, the June BOGO Sale was a familiar opportunity with a familiar constraint: a fixed, short window to convert demand into revenue, and a customer base large enough that reaching everyone with the same message was easy, but reaching the right person with the right message at the right moment was the harder, more valuable problem to solve. The team knew that in a sale this size, precision would matter more than reach; a broad send could still produce opens and clicks, but wouldn’t distinguish a customer genuinely close to buying from one who simply happened to see the message. With the sale’s short runway leaving little room to course-correct once campaigns went live, the opportunity was to identify high-intent shoppers upfront and put the sale’s full weight behind reaching them well. Specifically, the brand wanted to:

• Increase revenue contribution from CRM channels during the sale
• Improve campaign efficiency by targeting customers most likely to purchase
• Reduce dependency on blanket promotional broadcasts
• Identify high-intent shoppers using AI-driven customer intelligence
• Drive higher engagement and conversion across WhatsApp and Email
• Improve ROI through personalized audience selection

The Core Gap

Without a data-driven platform, segmentation for a base this size meant working in broad strokes, recent buyers, non-buyers, a rough geography or category split, since anything finer would have meant manually cross-referencing browsing history, past orders, and engagement across spreadsheets. That approach works well for always-on communication. A time-boxed sale like BOGO called for something sharper: a way to know, before a single message went out, which customers were genuinely close to buying, so the sale’s full marketing effort could be pointed at them from day one rather than spread evenly across the base.

Bacca Bucci worked with Netcore to replace manual audience selection with AI-powered affinity and predictive models that continuously scored, layered, and routed customers, covering the sale from pre-launch targeting through post-sale retention.

Step 1: Score Every Customer for Intent

Sending the BOGO offer to the full database meant reaching plenty of passive browsers alongside genuine buyers, driving up communication cost without a matching lift in conversion. Netcore’s AI Affinity Models addressed this by reading each customer’s historical browsing behavior, purchase patterns, product interactions, discount responsiveness, and engagement signals to produce a Discount Affinity Score. This isolated customers with a medium-to-high tendency to buy when a value-driven offer showed up, rather than relying on recency alone

Step 2: Layer Signals Into One Qualified Pool

A single score is still a guess. Netcore layered in three more signals on top of the initial affinity score:

• Purchase Propensity Models – identified customers with a high probability of purchasing within the next 7 days, and separately, within 14 days, based on recent signals like website visits, product views, cart activity, and campaign engagement
• Predictive CLTV Modelling – flagged customers in the Top CLTV Percentile, so premium promotional visibility went to customers likely to generate the most long-term value, not just the next transaction
• Repeat-Purchase Likelihood Prediction – surfaced existing customers with a Fast Repurchase Likelihood Score and recent purchasers showing strong brand affinity

Netcore combined all four signals, discount affinity, purchase propensity, predictive CLTV, and repurchase likelihood, with historical engagement behavior into one high-intent pool, so every customer targeted met more than one signal of genuine intent rather than a single loosely-correlated one.

Step 3: Split Treatment by Channel

This qualified pool was then split by channel. WhatsApp received the full high-intent audience, paired with urgency-led, offer-focused creative built for a fast scroll. Email was narrowed further, to customers with a history of actually opening and clicking previous emails, and soft bounces, hard bounces, and unsubscribed contacts were automatically excluded before every send, protecting sender reputation and deliverability rather than leaving that hygiene to a manual list-cleaning step.

Step 4: Orchestrate the Sale Across Touchpoints

WhatsApp and Email ran as a coordinated sequence rather than isolated blasts, creating multiple touchpoints to re-engage shoppers who hadn’t yet converted and deliver personalized sale messaging at the right moment across the BOGO campaign’s lifecycle, rather than a single one-shot announcement at launch.

Step 5: Retain and Re-Engage Beyond the Sale

Using Netcore’s RFM (Recency, Frequency, Monetary) segmentation, customers were grouped into cohorts, Loyal, At Risk, and New Enthusiasts, based on recent WhatsApp and Email opens, clicks, and purchase behavior. That gave the team a lifecycle structure for re-engagement, timely promotions, and personalized journeys that outlasted the sale itself, rather than starting from zero again for the next campaign.

Results are best read as three connected outcomes: how efficiently the sale spent its marketing budget, how much of total revenue CRM channels drove, and how well the AI-targeted audiences actually engaged.

Marketing spend worked harder

Targeting only high-intent, multi-signal audiences meant sale spend converted at a level broad targeting couldn’t match:

• 15X ROI on the BOGO sale campaign – every rupee of campaign spend returned fifteen times its value, directly improving the sale’s overall profitability

CRM became a bigger share of total revenue

Precision targeting didn’t just improve efficiency, it grew the CRM channel’s actual weight in the business:

• 3X growth in revenue contribution from CRM channels, taking CRM-driven revenue to an 18% share of the BOGO sale’s total revenue – meaning CRM moved from a supporting channel to a meaningful share of sale-period revenue

Customers engaged more with what they received

Because messaging was matched to intent rather than sent broadly, the audiences that did receive campaigns responded at a noticeably higher rate:

• 91% higher Click Rate on hyper-personalized, GIF-led WhatsApp communication built on AI affinity segments – showing that relevance, not reach, drove the engagement lift

Beyond the numbers

• Audience selection moved from manual, one-size-fits-all broadcasts to a continuously scored, multi-signal process the team can reuse for future sale events
• RFM-based cohorts (Loyal, At Risk, New Enthusiasts) gave the team a durable retention structure that extends well past the BOGO sale window
• Email deliverability improved by automatically excluding bounced and unsubscribed contacts before every send

Bacca Bucci plans to extend the same AI-led approach, affinity and propensity scoring, layered intent signals, and RFM-based retention, beyond BOGO to other sale events and everyday lifecycle marketing, treating this campaign as the template rather than a one-off effort.