Once upon a time, people were thrilled just to receive an eCommerce order in the mail, shipped from their favorite brand, as DTC fulfillment came into its own. Even if it took a week to get there, and looked no different than millions of other orders, the novelty was enough to carry the day and earn a measure of loyalty.
But that ship has long since sailed. In today’s fiercely competitive eCommerce market, personalization is not just a luxury, it’s a necessity. Customer expectations have risen to the point where the sameness of orders is a losing proposition. According to Salsify’s “Consumer Research 2022” report, 70% of U.S. shoppers are more likely to buy if a product page has personally relevant images, videos, text, and reviews.
The grail is creating personalization at scale — as a repeatable process enabled by technology, chiefly AI — but just how valuable is it? A 2019 McKinsey study estimated its value creation at $1.7 trillion (with a “T”), with $450 billion–$800 billion of that coming from retail. But again, thanks to technology, personalization at scale is more achievable than ever.
The Challenge of Personalization at Scale
The logistical challenges of DTC fulfillment personalization at scale include tailoring products based on individual preferences, which requires sophisticated distribution networks and inventory management to handle the diversity of goods. This level of customization often means higher material, manufacturing, and labor costs. And in terms of technology, achieving personalization at scale requires advanced analytics, AI, and machine learning to first accurately predict customer preferences, and then efficiently manage production processes.
Key Strategies for Personalized DTC Fulfillment
Let’s look first at some basic approaches to personalizing DTC fulfillment before exploring ways it can be scaled.
Leveraging Data and AI
Data analytics and AI can be leveraged to analyze consumer data and predict purchasing behavior, information brands can then use to tailor both product recommendations and packaging. AI algorithms take a close look at consumers’ past interactions, searches, and purchase history, and identify trends and preferences. Brands can then offer highly personalized shopping experiences.
Using this approach, both customer satisfaction metrics and sales increase, as shoppers are presented with products they’re more likely to buy. However, it requires a strong focus on data privacy and ethics to ensure transparency and user consent, to maintain trust and regulatory compliance. Brands must strike a balance between personalization and privacy, a critical factor as misuse of data causes reputational harm.
Custom Packaging and the Unboxing Experience
With a fine gourmet meal, as evidenced by any one of a number of cooking shows and celebrity chef programs, presentation is everything. Well, mostly everything – it DOES have to taste good, too! In much the same way, how a DTC order is packaged and presented to the shopper is kind of a big deal. And there are billions invested in marketing and branding research to back up this point.
This is especially true with subscription orders, where a monthly, curated assortment arrives with everything from wines to golf balls to dress socks. The unboxing experience is often shared across social media by a delighted consumer if the “wow” factor is there. But the concept holds true across eCommerce.
Some customization options include personalized notes, branded packaging, and as above, product customization based on preferences derived from data analytics.
Dynamic Fulfillment
Because the needs and requirements of eCommerce shippers often change based on a variety of factors, flexibility, and adaptability are key capabilities, whether fulfillment is happening in-house or through a 3PL partner. Technology can drive real-time process adjustments to enable greater levels of personalization, based on eCommerce order specifics.
On-demand warehousing is one solution designed to address this need. It involves outsourcing warehousing and fulfillment services by matching excess 3PL network capacity with shippers’ immediate needs through a software platform.
Smart inventory management systems leverage AI and real-time analytics to optimize e-commerce fulfillment on the fly. It does this by anticipating demand and adjusting stock levels. Fulfillment and delivery are optimized by efficient resource allocation and automating inventory adjustments at the SKU level.
Implementing Personalization at Scale
Granular analysis of real-time customer data, again using AI and analytics, enables customized packaging, delivery options, and product selection, without sacrificing throughput. Personalizing packaging doesn’t require a major investment in equipment to enable specialized wrapping or messaging, which creates a sense of exclusivity and brand engagement.
Gathering and analyzing customer feedback data also helps to refine the personalization process. This includes methods such as surveys, social media, and agent interactions gathered in a CRM system. Checkout options such as setting notification frequency and “I want to use less packaging” also feed into personalization at scale.
eCommerce Personalization No Longer A “Nice to Have”
Another data point from McKinsey’s research: brands that excel at personalization generate 40% more revenue than those that do not. So clearly, there is a ton of business value as an incentive to not only personalize, but do it in a way that doesn’t adversely impact the efficiency of eCommerce fulfillment operations.
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