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Direct-to-Consumer brands are popping up everywhere, redefining what customer interactions mean. In a world dominated by personalization,D2C eCommerce requires data analytics as a strategic arm to drive engagement and be what their consumers expect them to be.
The pandemic has created new opportunities and markets for businesses wishing to adopt the D2C model, particularly for those sellers who have a product with a unique value proposition. In fact, India is home to 800+ D2C brands. However, one drawback of being green and new to the business is that younger sellers have fewer resources than decades-long enterprises to maintain their visibility. This is why they have to be more deliberate in their customer acquisition and retention strategy. And this is where the right data analytics come in!
Analytics help D2C brands stay customer-centric by uncovering trends and shifts in consumer buying behavior, thereby enabling the brand to revise their marketing tactics. The idea is to make the best of the herd mentality by making both the product and post-sales experience memorable enough for customers! Let us take you through the advantages and applications of data analytics in the D2C landscape.
Where can D2C eCommerce Apply Data Analytics?
The right product will be considered the right fit only if you’re marketing it to the right users, and this relevance is cemented by data analytics. Some of the advantages of data analytics are
1. Staying updated with business-critical insights
Every brand is in business to make a profit. And for this to happen, the right decisions need to be taken at the right time. In the case of a brand that sells expiry-sensitive products, for example (think cosmetics, food and beverages, medicines), the inventory-expiry report within an automated inventory management software would help them sell quality-compliant products. Once you set the expiry date, those ones nearing the end of their shelf life would automatically be taken off, preventing the seller from shipping out items that are past their usable date.
2. Providing consistent and personalized user experience
Consistency is the benefit of an omnichannel strategy.The customer should find what they’re looking for no matter how their journey began and ended. For this to happen, the first step is to confirm your store, app/ website are synced in terms of the product price and stock. You’ll need a report on the inventory warehouse-wise to confirm that deliveries can go in instances where the customer pays for a product online and visits the store in-person for pickup. These interactions can be seamless only when sufficient pincodes in close proximity to a warehouse or fulfillment center are picked up, enabling packages to transit all the way to the right address.
3. Reaching Data-Driven Decisions
How your customers interact with your company determines the type of shopping they do, what they’re coming for and to bridge any gaps in the buyer journey. You can even use their preferences to market relevant items when they become available again at a different time and/or price. Data-driven decisions help D2C brands improve their capabilities, especially when you factor in that a customer’s options for experimentation become more diverse when more brands enter the market. By tracking preferences through factors such as location, history and trends you have ample evidence to confirm the direction of your acquisition strategy.
4. Building market-specific buyer personas
Buyer personas give your customers a face and personality. It lets you know what your users are looking for, their spending power and the likelihood of what they’ll spend their money on. This information is vital to devising a roadmap for product and service launches. The marketing team can accordingly communicate the messaging better and distribute the campaigns across the right channels to ensure maximum coverage that generates interest. Data analytics can create those personas that enable the brand to provide personalized shopping experience based on what motivates the personas.
5. Driving recommendation engines
Recommendation engines run on machine learning and natural language processing. It picks up a user’s browsing choices and previous purchases to deliver tailored recommendations. The data within eCommerce analytics facilitate a closer personal bond between brand and customer which makes a customer feel special every time they browse through the brand’s website or come across their preferred brand in recommendations on marketplaces.
6. Demand planning and forecasting
Data analytics help D2C eCommerce brands to look at historical sales and match it to trends to predict what will change. Staying foresighted prepares D2C bands in advance, and they can bring forward more SKUs or reshuffle them across sales channels by seeing the timings and where a consumer is likely to be. For example, if there are more users searching for and adding a product ‘A’ in the early hours of a particular day of the week on Amazon, the sellers can upload and update their listings to be featured in that timeframe to ensure customers don’t miss out.
Demand forecasting also lets brands revise their prices and offer add-ons, freebies or giveaways based on a price limit. Think about those sales where you shop for another $99 and get free shipping, or a goodies bag.
7. Better inventory management
Depending on how young the brand is, the recency of its entry and type of segment it operates in, not all D2C brands need several facilities or huge storage space all year-round. Data analytics can help you lock down on the number and type of fulfillment, distribution and warehousing options to ensure you’re not spending too much on only one aspect of logistics, i.e. capacity in locations that aren’t making you money. You have to consider where your prime real estate is because you’ll also incur expenses in wages for those staff you hire to man these centers, so it makes sense to restrict your inventory to those places that service your customers better. Also keep in mind that inventory can spoil or expire and lead to more losses if you don’t have the data on hand. With analytics, you can manage your inventory better in the locations you serve, and keep sufficient stock to meet demands.
8. Higher customer satisfaction
Customers are what makes, or breaks a D2C brand. And keeping them happy before, during and after the buying experience is what constitutes exceptional customer service. You can celebrate positive feedback and wins, but it’s equally important to factor in and act on negative feedback too. A bad review on review aggregator platforms can bring your score down, and ward off prospective buyers, especially when they see that the brand is evasive, unresponsive or simply unaware of the existence of poor reviews.
Based on data analytics, D2C brands can tie up with review sites and send out incentivised mailers for every rating and review received. This will club reviews by the time, date and type, and sifting through these helps you understand the number of issues encountered. Your support team can know what customers are struggling with and provide a more personal response for persistent issues, which can even persuade a disgruntled customer to change their minds.
How to leverage Data to Drive eCommerce Sales
- Unify and Centralize Data for Easier Assimilation
The first thing you’ll need is a centralized dashboard view of your sales, inventory, tax and order statuses. Order status refers to the number of items that are active, completed, failed or returned to the origin. Looking at this data lets you know what is and isn’t working, and makes the logistics trackable.
- Connect Both Figures and Customers
Simply gathering data won’t suffice. You’ll need to convert unstructured data to structured data and slot it in the right places to make sense of what you’re seeing. This way, you can establish a link between the numbers and patterns of customers. Unified data analytics merges data with AI to generate intel on possible outcomes.
- Know When to Take Action
A seasonal inventory can cause demand for a certain product to peak or decline at different points in time for a year. It’s essential to keep watch on these fluctuations in order to plan the sales pipeline accordingly. You can also revise and adjust your pricing to offload slow-moving inventory quickly through bargains, charity drives and clearance sales. Shelf-wise reports can help you the prUnderstanding seasonal patterns & trends might assist you in determining how things will pan out throughout the year. As a result, you’ll be able to focus on the right products that are available at the right time to meet your customers’ expectations.
- Reading Data to Understand Website Shopping Behavior Flow
Website behavioral analytics lets you monitor how a customer interacts with and transacts on your website, from the moment they land, browse through and checkout. This data helps you understand the purchase behavior flow and reveals where engagement is minimal or maximum, thereby bringing up a path that leads to conversions. Shopping behavior flow is like learning to read minds,because it lets you predict the future by observing current patterns.
- Use product performance data to track and improve
The key reports within an eCommerce solution that helps D2C sellers optimize their inventory and orders would be the inventory aging, order aging and SKU performance, which work as follows;
- Inventory aging: this report displays the number of units available for a specific time duration that is yet to be sold, and therefore available.
- 2. Order aging report: The order aging report lets a D2C company see the number of days for which an order placed by the customer has not been shipped yet, enabling you to get to the cause behind the delay and expedite the process.
- 3. SKU performance: The SKU performance lets you track product performance for a set time period. Through this report, sellers can know which categories sell well or underperform, and can accordingly adjust their promotional and pricing strategies to draw or spread the attention.
Performance data extends to confirmed and pending returned items too. If your rate of return is higher than normal, you can investigate the causes behind it and proactively minimize future recurrences.
How new-age brands are leveraging data analytics to power D2C ecommerce
D2C brands, both established, and newcomers are realizing the role data plays in the digital world, which is why data analytics is the first thing they look for in an AI-driven eCommerce solution.
eCommerce analytics is behind every step a business takes to grow. The sheer size of data brands are dealing with requires a system that can split up the reporting to different aspects of logistics, in order to avoid confusion when reading the report. The reports should not just be accurate but should also make sense to even beginners who are unused to number crunching.
With analytics, a D2C brand can leverage insights that help them to save costs, achieve higher conversion rates, satisfy their intended consumers and optimize logistics. The business can periodically appraise their performance based on metrics, such as earned revenue, time-to-order fulfillment, support tickets raised and resolved per day, cart abandonment and returns reports.
