What’s so challenging about hyper-local ecomm businesses?
Let’s take grocery brands, for instance. Customers transact frequently, a typical cart is likely to contain perishables, per-unit product-value is small. For brands dealing in cold-chain dependent products like milk, meat etc., supply chain constraints also come into play.
Another characteristic of hyper-local ecomm is their competition — the unorganized sector — essentially, the neighbourhood ‘baniyaa’. Since the category is so commoditized, brands find it doubly challenging to deliver value. Convenience can draw in customers initially. However, scaling would require rapidly climbing Customer-acquisition costs.
Given these characteristics, what can help such businesses scale exponentially?
“What got you here, won’t get you there”
To begin with, recognize that hyper-local, by its inherent nature, means hyper-personalization. Each geography, each state within that geography, each city within that state, each locality within that city — is likely to present unique characteristics.
Next, accept this reality and drive a Retention-focus across functions in the organization, from Day 1. Be it customer acquisition/ sourcing/ delivery/ marketing/ offer development — every aspect of the business has to fervently cater to this reality. There is really no point attempting to scale; without steady focus on customer retention.
Metaphorically speaking, this means making Customer Retention the growth-engine and Customer Acquisition, the fuel.
Take a few steps at a time
India’s diversity is much-spoken of and well-documented. Build a city-by-city playbook of rules, to deal with this reality. Considering the nuanced nature of Hyperlocal, a great starting point is a well-detailed product-locality fit. A product mix that works in one locality might not, in another. The first step is to understand local needs, then build a product mix to service that need.
When rolling out in a large geography (say, a metro city), start small. Identify 2–3 core geographies, build an understanding of customer needs in these geographies, crack these geographies in terms of attracting customers; then move on to the next cluster of geographies within the city.
Understand that single factor which drives hyper-local trial in each geography. For instance, customers in larger cities might be seeking a truly differentiated Product; whereas for those in transportation-challenged smaller cities, Convenience might be THE key driver.
Loop customer data into business understanding
The advantage of recurring data from the same customer means you can gain a ‘linear’ understanding of each customer’s on-platform behaviour. Mapping customer journeys helps identify drop-off points, as also understand context of customer needs. For instance, at what point in the browsing experience does a customer of a certain profile typically drop off? Therefore, what is the best recommendation to make to that customer, to ensure conversion? The end-objective is to make every purchase experience a ‘zero click’ process.
Furthermore, building context into on-platform communication can go a long way in retaining customers. Effectively designed Push Notification campaigns have been known to deliver as high as 4x or 5x conversion rates. There are various ways of building context into on-platform communication. For instance, customers visiting a particular product page can be prompted through to purchase, with simple text-prompts:
– offering them related products (‘Here’s what others looking for this product bought’) or
– offering help in product discovery (‘Did not find what you’re looking for? Ask us over chat’) or
– offering to inform (‘Set an alert for when this product becomes available’) and so on.
Create a habit-forming experience
‘Habit-forming’ essentially means building elements into your offer, that trigger revisits to your platform, continually. This can be achieved primarily by offering a seamless browsing experience and a relevant product portfolio.
To create a seamless experience, create a loop using behavioural data, to pre-empt purchase, thereby reducing the customer’s reordering cycle. For instance, past data will indicate how frequently a particular product is purchased. This understanding can be used to build prompts on your platform, to remind the customer to purchase the same product again, even before s/he feels the need for it.
An important side-note: while customers buy hyperlocal online, they also impulse-purchase, offline. For many hyper-local digital businesses, primary competition is not another brand; instead, it is the Offline format. What helps is to put in place a baseline persona of your customer, so you can predict his next product-basket, recommend it on-platform and thus, ensure s/he buys it online. Once customers are habituated to the convenience of the online experience is, their offline habit is likely to recede.
Habit formation can also be achieved through product portfolio offered. Offering unique products can help attract loyal customers. These customers can be latched onto, by building an offline presence. Many digital brands successfully build an offline presence, primarily to ensure that they do not lose customers to traditional retail.
ThinkBumblebee applies an ‘outside in’ lens, combining analytics with diverse disciplines like semiotics, consumer psychology, social data etc. Reach out, to discuss how our understanding of Hyper-local data has helped brands scale as well as improve retention rates.