The Path to Customer Focus – Magazine Articles
The key to success is build a customer-centric business plan:
- Project revenues from existing customer base.
- Determine the number and type of New customers must achieve the plan.
- Triangulate with category, channel and marketing plans.
At the heart of this new model is an explicit trade-off between growth and profits: accelerating customer acquisition can reduce short-term profits but stimulate long-term growth; alternatively, reducing customer acquisition will have the opposite effect. There is no right answer, but smart retailers are clear on whether they are trying to generate cash, medium term profits, or long term growth and can then adjust their trajectory accordingly. Too many retailers make the mistake of comparing like-for-like growth rates, creating unrealistic top-down targets, extrapolating from historical rates, or focusing too much on the most important sales. Once the overall goal is set, retailers should define plans for categories, channels and marketing based on customer results:
- Marketing: Distribute marketing spend among different marketing touchpoints to optimize customer acquisition and retention.
- Channel: Define customer acquisition and retention goals by store and online.
- Product: build a range based on products / brands / categories aligned with customer acquisition and retention. Assign range and size ratios to stores based on the characteristics of local customers.
- New business decisions
The actions of retailers are typically brutal, based on sparse data and dependent on physical execution, and primarily taken at the aggregate level of stores, categories or customer segments. Thirty years ago, the advent of IT gave retailers the ability to rethink processes, but success required process reengineering – if retailers simply computerized their existing processes, they were missing out on the opportunity. New technologies now give companies the opportunity to rethink their decisions.
Some decisions will remain the same, but digital levers can be used to transform their effectiveness, frequency or uniqueness. For example:
- Decisions that required manipulating data in spreadsheets can now be fully automated.
- Decisions that were historically made every week (at a trading meeting) can now happen every day or every hour.
- Decisions that were historically made at the category level can now be made (and executed) at the product or even SKU level.
But many trading decisions will have to be completely rethought with a different logic. For example, if a product is overstocked, retailers must now decide to increase its exposure (more marketing), trigger a customer-specific promotion, or offer a price discount? More generally, retailers must now review their key business decisions from the perspective of customer profitability.
- Marketing: are we optimizing the profit of the session versus the client LTV?
- Channel: Are we making decisions on the basis of four wall profit versus customer profit in the catchment area of ââthe store?
- Product: Are we focusing on the profit of the season versus acquiring customers?
HOW TO RETHINK DECISIONS
- New customer-centric metrics and reports
Retailer reports have traditionally focused on aggregate average results– for example, comparables, balances, stock rotations – which are used to tell a simple story. There is a clear picture of performance across stores, across categories, between shoppers and between managers. The metrics are mature and the benchmarks are numerous and significant. This made sense in a world where aggregate data (for example, at the store or category level) aligned with the frequency and specificity of the decision made. In addition, the aggregation of data in physical commerce has a naturally homogenizing effect that makes averages useful. The changes described above now require a different approach given:
- Focus on profit – reports need to be broken down to understand the drivers of profit. It’s easy to generate income and cut profits in a customer-centric world.
- Faster and more specific reporting – reports should align with frequency of actions and should make sense of millions of customers and customer-centric actions. The key here is to measure the inputs as well as the results.
- More granular – digital data provides incredible detail on every impression, click, visit and customer transaction, requiring a reduction in the average of reports to understand what drives performance.
Unlike physical commerce, aggregateaverages are the enemy of the customer-centric retailer– they are generally unnecessary, often misleading and rarely representative. Retailers should review their key trading reports and metrics to ensure that:
- Measured things that matter to customers and drive action [what Amazon calls âcontrollable input metricsâ]. A good example is page-weighted availability for high value customers – are you stocking up with the products high value customers are looking for?
- Reports focus on outliers and anomalies– highlighting waste and inefficiency is essential to understand what can be improved. For example, how much money do you spend on digital marketing for sold out products?
- Metrics are on average– by store, by SKU, by customer – to understand at what level to act. For example, how often do you take a product-level action when the issue is at the SKU level?
NEW APPROACH TO REPORTING
Retailers no longer have the luxury of not wanting or not being able to change. Anyone who takes this transformation seriously will recognize how radical and profound these changes must be in their organization. Activating the new information, new plans, new decisions and new metrics needed to create a new customer-centric operating model cannot be accomplished by small, superficial adjustments.
To truly put customers at the center of the business, it takes competent leadership, such as a customer director, who can transcend silos and channels with the big picture in mind. Navigating with AI and data science at the heart of the organization, managers must have the AI ââskills and understanding that will then enable them to successfully achieve the necessary balance between human and human-based decision making. AI algorithms. Mistakes and bumps in the road are inevitable. Transformation is an important challenge, not to be underestimated. It is imperative to create a culture where these bumps are seen as opportunities to learn and transform in order to foster growth. Skilled, agile leadership and culture, along with a tech-empowered employee base, are essential elements for embarking on a journey of innovation and ultimately a successful (and profitable) future.