In the world of eCommerce, where margins are wafer-thin and maximizing revenues is paramount, Category Managers are the unsung heroes who orchestrate this entire opera seamlessly. From boosting sales and optimizing profitability to managing inventory and strategizing for category expansion, their plate is always full.
The relentless pursuit of revenue
However, amidst this bustling orchestra of tasks, there’s one relentless quest that drives their daily grind:
the pursuit of revenue growth and profitability
Through our extensive conversations and engagements with Category Heads, we’ve come to understand that revenue is the daily conundrum they tackle head-on. It’s a multifaceted challenge with numerous moving parts, demanding their unwavering attention and precision.
Every day, the Category team embarks on a journey to uncover the factors that may be impacting revenue. And it’s not just a cursory glance; it’s a structured deep dive, a systematic unraveling of the “Whys.”
Let’s explore a real-life example to understand what structured revenue problem-solving looks like in action.
Structured revenue problem-solving in action
Meet Anurag, a Category Head at an eCommerce platform. He notices a concerning dip in the platform’s weekly revenue, and he swiftly turns to Naman, his category manager, to get to the bottom of it.
Naman immediately dives into the “Why” behind the revenue drop …
In eCommerce, such declines are often localized hiccups, so he begins by slicing and dicing data into city clusters. Once he pinpoints these hotspots, he zooms in further, dissecting revenue distribution by product categories within these clusters.
Naman doesn’t stop there. He pores over revenue figures to identify which brands have taken the hardest hits. As the puzzle pieces start falling into place, he zeroes in on one of the major contributors to the revenue slide. In Mumbai, the detergent segment of a specific brand, Tide, has taken quite a hit.
Now that Naman has identified the area of focus, he may need to navigate a multifaceted decision tree to identify the precise root cause that requires attention. He delves deep into the SKU level, breaking down the revenue metric to determine whether the decline originates from a decrease in sales volume (GMV) or a dip in profit margins.
Revenue = GMV (Sales Volume) x Profit Margin
GMV and margin are complex metrics, influenced by several component metrics. To truly grasp their dynamics, these metrics must be examined at a granular level.
Let’s take GMV as an example.
GMV = impressions ✕ conversion rates ✕ pricing
Now this equation might look simple, but drilling into the components is an intricate task. More often than not, it's not a single factor but a combination of them that influences the outcome.
For example, if impressions have taken a hit, it’s essential to investigate further: Did the drop in impressions primarily occur on the homepage, or has the individual product page experienced a decrease in visitors? Is the issue related to how products are displayed or promoted on the platform?
Likewise, multiple factors influence margin:
Margin = base margin error ✕ ongoing clearance sales ✕ increased penetration of targeted coupons
Additionally, a Category Manager needs to see the cost-benefit between the addition value generated vs. the revenue loss incurred.
Picture Naman in the real world, working his way through this decision tree, where several cluster->product category->SKU pairs are playing a role in the revenue decline. For each of these pairs, Naman must repeat the entire process, straining his ability to take swift, impactful actions.
Challenges in the daily grind
These prioritization efforts and the subsequent traversal of the metric tree illustrate the intricate and demanding nature of the Category Managers’ daily roles. They find themselves repeatedly immersed in this complex process, which, given the extensive data analysis involved, consumes a significant amount of time.
However, despite their best intentions, it is not uncommon for Category Managers to resort to gut-based or surface-level approaches, drawing from their past experiences and historical data to make decisions. Unfortunately, these approaches don’t always yield optimal results and may not align with the overarching organizational objective — a concern for Category Heads.
In fact, one of the main goals of Category Heads is to optimize processes for frontline teams, aiming to make their daily responsibilities not only more manageable but also highly actionable.
A better approach: Empowering Category Heads with productized frameworks
Imagine if we could automate the problem-solving frameworks used by the most experienced minds within the Category Team, freeing operators from the daily grind and ensuring that actionable insights are instantly available to them.
GobbleCube — a purpose-built platform for brands to run revenue — precisely does that. It’s akin to having an AI co-pilot that does the heavy lifting on our behalf.
And the best part: leaders have full visibility into revenue opportunities, potential leakages, and trends.
This could empower Category Teams in several ways:
- It enables teams to instantly identify the root causes of revenue problems, giving them ample time to strategize and devise effective solutions.
- Armed with knowledge of the actual root cause, Category Managers can adopt a consistent problem-solving approach that aligns with the organization's overarching revenue strategy.
- Category Heads can have confidence that their teams are focusing on execution instead of getting bogged down by data analysis.
If this sounds interesting, then give us a shout. We’d be happy to chat!
