How to Successful Shift to Digital-First Retail eCommerce

In the past year, retail has evolved, unlike any other industry. As eCommerce continues to grow, the shift to a digital-first world has fully arrived. This transformation requires deep expertise to get it right — and it starts with your tech stack.

How to Successful Shift to Digital-First Retail eCommerce
How to Successful Shift to Digital-First Retail eCommerce

Retail is unlike any other industry, it is complex and ripe for innovation. Over the past few years, enormous changes have permanently transformed retail into an ultra-competitive and digitally fluid landscape. This shift has created a new sense of urgency around digital transformation and ultimately the retail martech stack.

Table of contents

How to Use this Guide
Why You Need Technology Built for Retail
Building Your Retail Marketing Technology Stack
5 Characteristics of the Retail Martech Stack of the Future
Technology Must-Haves for a Best of Breed Retail Martech Stack
How to Measure the Value of Your Technology
Outcomes of a Best of Breed Retail Marketing Technology Stack
Sephora Improves Data Activation and Accessibility to Strengthen Loyalty
Hammacher Schlemmer Hones Personalization to Grow Digital Revenue
ASICS Reduces Size Sampling, Increases Conversion and Keep Rate with Personalized Digital Experiences
Making Changes in Your Organization

The Retail Marketing Tech Stack Guide, co-authored by Bluecore, Google, and True Fit, is designed to help retailers introduce the necessary marketing technology to compete effectively in this modern retail environment.

With that in mind, The Retail Marketing Tech Stack Guide breaks down what to consider when making marketing technology decisions in today’s new retail environment:

  • The importance of technology purpose-built for retail
  • How to build out your retail martech stack
  • How to get started on making this type of change in your organization

ASICS, Sephora and Hammacher Schlemmer share how they approach building a digital-first tech stack to grow revenue and outperform the competition. In this guide, Bluecore, Google, and True Fit breakdown what to consider when making marketing technology decisions in today’s new retail environment.

As you decide to start building out your modern retail martech stack, we hope you find this article insightful.

How to Use this Guide

Retail is unlike any other industry. It is ubiquitous, complex, and ripe for innovation Over the past several years, enormous changes — such as the continued rise of eCommerce and mobile, the introduction of direct-to-consumer and subscription buying models, and the onset of a global pandemic — have permanently transformed retail. The result is a more global, ultra-competitive, and digitally fluid retail landscape.

The overall unique nature of the industry combined with this large-scale transformation makes retail even more complex, requiring deep expertise to get right. Strategies for everything from merchandising to marketing to fulfillment are evolving at a rapid pace, all to engage highly discerning and fickle consumers and turn them into loyal customers.

Against this backdrop, everything must get smarter and more efficient. Smarter to work toward retail-specific goals, such as improving sell-through, maximizing margins, growing repeat purchase rates and reducing returns, and to improve 1:1 personalization to meet customer demands. More efficient to accomplish those initiatives at scale, reduce waste, and increase returns on technology investments.

When it comes to achieving these goals in smarter, more efficient ways, retail specificity matters. Moving into an AI-driven world will help accomplish key measures around intelligence and efficiency, but only if those AI models can go deep on specific goals. And for that to be possible, the technology needs to be built for retail. Further, many follow-on benefits come from introducing technology built for retail, including deep expertise in strategy for how to best put that technology to work and prioritization of retail-specific requirements on the innovation roadmap.

Critically, the time to make these changes is now. This guide is designed to help retailers introduce the necessary marketing technology to compete effectively in the modern retail environment. To do so, it explores:

  1. Why having technology built for retail is so important
  2. How to build out your retail martech stack
  3. What outcomes to expect from introducing these types of best of breed solutions
  4. How to get started on making this type of change in your organization

Why You Need Technology Built for Retail

First and foremost, it’s essential to understand the value of retail-specific technology. Traditionally, most technologies were industry-agnostic or “horizontal,” meaning it was built to satisfy use cases for a variety of industries. Marketers in retail, finance, manufacturing, and so on would all use the same solution, under the assumption that the consumer purchase cycle is the same across the board. But in reality, we know that’s not the case.

How consumers buy retail products is quite different from how they buy financial products, which is also quite different from how they buy hospitality services, and so on. As a result, it doesn’t make sense for platforms that manage consumer data for marketing throughout the purchase cycle to have the same workflows and out-of-the-box capabilities across these verticals. This is especially the case as companies move from channel-first to consumer-first strategies, which has made how people buy a critical part of responsive, personalized marketing programs.

Ultimately, this shift has led to a situation in which horizontal solutions that try to satisfy the needs of everyone ultimately end up satisfying no one. They typically leave marketing users across different industries frustrated as they piece together workarounds to create personalized experiences for their unique consumer purchase cycle, all because they’re attempting to make the technology work in ways it simply wasn’t intended to. This recognition has led to the rise of vertical technology that’s designed to meet the highly specific needs of a given industry. For any type of technology, a vertical-specific focus allows for deeper use cases to solve a more concentrated set of problems (as opposed to the shallow, surface-level approach of horizontal solutions).

Take as an example Veeva, a CRM solution designed specifically for the life sciences industry that offers workflows to help manage clinical trials, regulatory submissions, medical affairs, and patient engagement. Veeva’s vertical focus makes it uniquely positioned to solve challenges specific to this industry, which has helped life sciences organizations achieve key outcomes like bringing products to market faster while maintaining compliance. Organizations realize enormous gains in these outcomes because Veeva is purpose-built to solve highly specific challenges and natively understand the types of data and goals driving life sciences organizations.

This type of depth provides value in and of itself. However, it becomes even more powerful in an AI-driven world. In today’s environment, data is precious, and that’s becoming even more true as AI-powered technologies become more mature and their adoption of them grows. AI requires data to train models to optimize for specified outcomes, and the more data it has as well as the more specific that data is to the targeted outcomes, the stronger those models will perform. Getting the necessary volume and specificity of data to strengthen performance requires a vertical focus.

In fact, the key to good AI is focusing it on (and training it to master) one very specific problem set for a specific vertical, use case, or user type. That’s because different verticals deal with different types of data and optimize for different goals — all of which limit AI models’ ability to learn and improve over time. Think of it like mastering an instrument: You’ll get much better, faster if you focus on just one instrument versus trying to learn how to play multiple instruments at once.

As a result of this depth, retail-specific technology can drive key outcomes around:

  • Surfacing more conversion opportunities
  • Turning shoppers into lifetime customers, versus driving single transactions, by identifying shopper level optimizations for repeat purchases
  • Accounting for engagement across channels, as retail happens on more channels than any other vertical
  • Optimizing for increased margins and sell-through as well as reduced return rates

Beyond the improved power of the technology itself, introducing technology built for retail technology comes with additional benefits around the team supporting the solution. For example, technology partners that offer solutions built specifically for retail will employ retail experts, resulting in more hands-on advice around key goals and use cases from your account team. Additionally, it means that retail features will always get prioritized on the product innovation roadmap since there’s no competition from features designed to help teams in other spaces (e.g. finance) that provide little-to-no value for retailers.

Building Your Retail Marketing Technology Stack

As you begin to build out and improve upon your retail marketing technology stack, one of the most important things to remember is that it’s not just about having the right technology — it’s also about using that technology effectively to achieve key goals.

With that in mind, let’s explore what to look for in retail marketing technology and how to use those solutions effectively together to create a true best of breed retail martech stack. The retail marketing technology stack of the future is a modern set of tools on which retailers will come to rely to intelligently and efficiently achieve key outcomes, such as increasing customer loyalty. Regardless of the exact composition of any given brand’s retail tech stack, five characteristics must be present for success.

5 Characteristics of the Retail Martech Stack of the Future

  • DIGITAL FIRST & CLOUD-BASED: Regardless of your brand’s origins, everything in retail is quickly becoming direct-to-consumer and digital-first. Your technology stack must be equipped to meet this new normal, and as a result, the retail marketing technology stack of the future is built around digital as the primary channel. In fact, many retailers are already moving to a cloud-based infrastructure, like Google Cloud, that provides the flexibility and scalability needed to meet the needs of growing digital experiences.
  • HIGHLY AGILE: Agility is essential to success in the ultra-competitive and disruptive retail space. The ability to quickly pivot the business to respond to unexpected events — whether that’s a major shock to the system like COVID-19 or a smaller event like newly trending products — will separate the winners going forward. This makes agile processes that empower marketing users to take action quickly a critical characteristic of any modern retail technology.
  • PERSONALIZED: Consumers now expect highly personalized and seamless digital shopping experiences as they move across channels. This expectation has resulted in the demise of channel-based marketing in favor of customer-based marketing that creates unique experiences for individual shoppers, regardless of where they are, as opposed to designing experiences around channels. Meeting this imperative requires technology that stitches together three key types of retail data (customer, behavior, and product data) across the full lifecycle from discovery to purchase so that it’s manageable, accessible, and actionable from a single place. Importantly, you either need a highly extensible system that integrates all your other technologies to make this centralization of data possible or you need a single system that can house those types of retail data.
  • BUILT FOR RETENTION: Loyalty is actually retailers’ best acquisition tool. Prioritizing customer retention and loyalty can help grow bottom-line revenue, increase market share, and create raving fans that make acquiring new customers less expensive. To achieve this goal, your team must use technology that’s built for retention, meaning solutions that help develop a deep understanding of your customers through first-party data. Your marketing team can then use that information to better engage shoppers, all with the intent of building relationships and driving continued repeat purchases (rather than just looking at each purchase as a single transaction).
  • DRIVEN BY DATA ACCESSIBILITY: Real-time access to data and the ability to act on that data in an intelligent, automated way is replacing manual segmentation. Data segmentation works when you have a large dataset about something that happened in the past, but it doesn’t help predict things like trending products or shopper behaviors so that you can respond to them in moments of need. In contrast, having easy access to actionable data allows retail marketing teams to create more timely and valuable experiences based on customer and product needs. For instance, this type of accessibility helps achieve goals like sell through without having to resort to discounts. It does so by providing the ability to (a) better predict inventory needs and (b) move that inventory through timely, value-based marketing.

Technology Must-Haves for a Best of Breed Retail Martech Stack

There is no such thing as a one-size-fits- tech stack for retailers. The exact composition of your martech stack will depend on a variety of factors that span everything from the size of your team and your brand’s growth trajectory to your top-line goals for the business and your existing areas of strengths and weaknesses.

That said, there are certain components that every brand needs to build a modern retail martech stack that delivers value around digital agility, centralization, retention, and data accessibility to help grow the business. Specifically, a best of breed retail martech stack must have four critical layers:

Business-Critical, Performance-Driven Layer

The best place to start when building your martech stack is with business-critical solutions designed to drive retail performance. These types of solutions should enable advanced digital personalization that allows your team to engage customers throughout their entire lifecycle.

This layer is one of many that comprises a best of the breed tech stack, but it’s the best jumping-off point because it is among the most unique to retail and provides a good base around which to introduce infrastructure and additional value-add solutions.

This technology should unify customer, behavior, and product data to provide marketers with easy access to consolidated information (e.g. a single view of customers along with details like their preferences, purchase history, and predicted next purchase) as well as the ability to take action on that data in customer-centric campaigns. Specifically, it should offer:

  • Strong command over first-party data, including the ability to unify customer, behavior, and product data and make that information accessible and actionable for marketers across key engagement channels like email, social, paid media, and the eCommerce site
  • The ability to natively integrate with and surface actionable insights against product data in real-time to improve product recommendations, power more intelligent merchandising triggers, and inform merchandising decisions
  • Advanced, AI-driven predictive models that help understand more about customers throughout their entire lifecycle and power timely personalization across channels in pursuit of key goals like retention and loyalty
  • Real-time feedback loops that use AI to adjust campaign elements (e.g. products, offers, content) based on each individual’s engagement over time, optimize for specific outcomes (e.g. clicking an email vs. opening it or preserving margins vs. increasing overall purchases), and better engage shoppers based on preferences for things like timing and channel, even as they evolve
  • Optimized workflows that simplify and automate processes like creating audiences, building email templates, and launching/managing campaigns
  • High levels of extensibility to seamlessly integrate with cloud data and digital experience solutions

CLOUD-BASED, E-COMMERCE LAYER

As shared in a recent Google Cloud blog, the shift to eCommerce accelerated at its fastest rate ever in 2020. And as this trend continues, it will be essential to have a cloud-based, eCommerce layer that makes it possible to scale capacity quickly and provide a modern customer experience.

Specifically, Google Cloud recently shared with Chain Store Age how this type of cloud-based, eCommerce layer should help make the supply chain more predictive and responsive to changing demands, particularly as the shift to digital accelerates. It also allows for quick pivots in response to sudden shifts in customer demands and external factors. For instance, in response to COVID-19, retailers had to scale online operations quickly, and those with cloud-based, eCommerce technology were able to do so most effectively thanks to the flexible and scalable nature of cloud solutions.

Going forward, Google Cloud expects a renewed focus on business continuity, and cloud capabilities will continue to be an important part of that conversation. As Google notes in a recent conversation with CRN, that’s because, with these types of cloud solutions in place, your team can focus on growth functions, like delivering the best possible customer experience and growing the business, rather than administrative elements, like worrying about accessing IT or business resources on-premise, deploying hardware and maintaining servers.

PERSONALIZED CUSTOMER EXPERIENCE LAYER

Currently, more than two-thirds of shoppers are buying online for the first time, and more than half are spending more online. An influx of online shopping presents retailers with an opportunity to engage with both new and loyal new customers in meaningful ways. Enhancing shoppers’ experiences with data-driven personalization throughout the customer journey reduces friction and yields a positive brand touch that impacts business.

As retailers innovate at a much faster rate it’s important to think about how to personalize the entire customer journey, from awareness through purchase and post-purchase stages. Connecting data about the shopper, including their fit and style preferences, as well as their shopping behaviors beyond your brand, to a brand or retailer’s own product and transaction data, allows said brand or retailer to generate a customer experience that is unique to each shopper.

Retailers who offer data-driven personalization find that shoppers view 2x – 3x more styles per session, AOV increases by 20%, and net incremental revenue lift increases by 3% – 6% sitewide.

EXECUTION LAYER

Finally, comes the execution layer, which should be a commoditized infrastructure with the right business-critical and cloud solutions in place. The execution layer has traditionally been among the places where marketing teams start when building out their technology stacks, but that will change in the modern technology landscape.

Previously, this was the case because building out a technology stack was like finding an empty lot and building an entire house from scratch. But the combination of modern vertical-specific business-critical solutions and cloud-based, eCommerce technologies have changed this by making it so that you can begin with a “starter house” as a base and then customize it to your needs. This shift not only saves effort, but it also means your team can spend less time stitching together different technologies and instead focus on being an expert in your business.

Because these execution technologies have become so commoditized, this should be the last area of focus in building out a modern retail martech stack. Instead of weighing technology decisions based on elements like sending infrastructure (which any cloud solution will support), your team should index toward performance-driven elements like predictive intelligence, real-time feedback loops, and vertical specificity.

How to Measure the Value of Your Technology

Once you build your modern retail martech stack, how do you evaluate its performance? You need to track certain metrics to identify if you made the right investments and measure the value each solution delivers.

Traditionally, marketing teams have focused primarily on short term consolidation and cost efficiency over measures like compound growth that evaluate incremental revenue over time. However, this focus has resulted in tradeoffs, such as lengthy implementations that require significant human capital, slow turnarounds on returns in investments, and the need to hire more people to manage this technology.

Going forward, this measurement focus — and, as a result, the way technology decisions get made — will need to change. For modern retail marketing programs built around best of breed technology, the most important points of measure will center around incremental revenue growth as well as cost and time savings (in other words, doing more with less).

With this focus in mind, some of the most critical points of measurement for the modern retail martech stack will be:

  • Time from Opportunity to Campaign: This should be less than one hour to give teams the necessary speed to stay agile and react quickly to changing situations, such as trending products, customer demands, and external events.
  • Percent of Personalization: At least 90% of campaigns should be personalized with 1:1 products, content, or offers to create truly relevant experiences for shoppers at every stage of the product discovery lifecycle. This level of personalization delivers the biggest returns on investment and performance increases. For example, data from Bluecore reveals that retailers who personalize 90%+ of campaigns see a 188% increase in conversions and 456% lift in revenue per email compared to retailers who employ a more even mix of personalization vs. static elements within email campaigns.
  • Level of Automation: At least 50% of elements within any given campaign should be automated to achieve the necessary speed to market and properly scale intelligent personalization.
  • Continuous Feedback: Performance-driven technology should deliver an automated, continuous feedback loop that regularly improves campaigns to optimize for specific goals based on each customer’s engagement with previous outreach.
  • Performance Model: Each technology’s pricing should align with performance, rather than volume, to ensure shared goals between your program and your technology partners.

Outcomes of a Best of Breed Retail Marketing Technology Stack

Introducing a best of breed retail marketing technology stack can yield enormous benefits. From meeting top-line objectives around increasing digital revenue and growing customer loyalty by unlocking access to data, the opportunities are plentiful.

Three retailers in particular that have already made these types of investments illustrate what’s possible.

Sephora Improves Data Activation and Accessibility to Strengthen Loyalty

Sephora is a leader in global prestige retail, teaching, and inspiring clients to play in a world of beauty. While Sephora had collected rich client data for years, the digital marketing team faced obstacles activating this data for use in marketing campaigns in a timely fashion.

Recognizing the opportunity to do more, the Sephora team began to look for new ways to activate data to engage with clients in ultra-relevant ways. The retailer already used Bluecore as a business-critical, performance-driven solution to power a variety of triggered emails and Google Cloud as a cloud-based, eCommerce layer, and they immediately saw how they could further tap into the same solutions to improve data activation and accessibility. Specifically, Bluecore and Google Cloud helped Sephora:

INCREASE LOYALTY AND BUILD REVENUE OPPORTUNITIES THROUGH A TARGETED “NEXT BEST CATEGORY” DATA MODEL

Sephora determined that cross-category shoppers were more loyal and had a higher lifetime value than single-category shoppers, and this recognition created a new goal for the marketing team to convert clients into additional categories.

To do so, Sephora partnered with Bluecore’s Data Insights team to build a highly targeted custom data model that ingests past purchase data and uses it to recommend the next best purchase in a new category based on common buying patterns. Sephora used this model in post-purchase emails, working closely with Bluecore to tweak the model and optimize results. Notably, this campaign resulted in an 8.4% increase in revenue per client and a 6.3% increase in conversions per client.

SCALE TARGETED CAMPAIGNS BY EMPOWERING MARKETING TO ACCESS AND ACTIVATE DATA

Bluecore and Google Cloud also helped the Sephora marketing team scale targeted campaigns like “Next Best Category” and do more with what they have by improving access to data and making it easy to turn insights from that data into action.

While Sephora was already in the mindset of getting more targeted with their marketing and has a strong analytics team in-house that can build models, Bluecore and Google Cloud give the marketing team direct, real-time access to that data. This access has enabled the team to execute, test, and optimize digital marketing campaigns on their own.

Hammacher Schlemmer Hones Personalization to Grow Digital Revenue

Hammacher Schlemmer is America’s longest-running catalog, founded in 1848 and providing a wide variety of unique products that solve problems for consumers. While the retailer honors its 170+ year legacy, it also keeps an eye toward the future.

Most recently, this drive for innovation-led Hammacher Schlemmer to double down on personalization to improve digital shopping experiences and grow revenue. Hammacher Schlemmer consolidated onto Bluecore as its full ESP to make this happen. Since then, Bluecore helped Hammacher Schlemmer:

GROW EMAIL REVENUE THROUGH INTELLIGENT 1:1 PERSONALIZATION

Hammacher Schlemmer achieved 16% year-over- year revenue growth in email and a 28x ROI in email by using Bluecore to activate customer data to power intelligent and automated personalized campaigns at the individual level. This personalization includes the ability to connect shoppers with products they’re interested in based on both past and predicted behavior and to build audiences based on category and discount affinity for targeted sends.

Most recently Hammacher Schlemmer has seen the biggest success using Bluecore’s Smart Campaign™, which automates the build and delivery of personalized emails. This unique type of campaign combines the basic idea of a batch email (a broadcast announcement or weekly send not based on customer behaviors or changes to products) with the functionality of a triggered email (an automated email that gets set up once, runs on its own and features dynamic recommendations).

EXPAND REACH AND AUDIENCE WITH A PURPOSEFUL CROSS-CHANNEL MARKETING STRATEGY

Bluecore unlocked so much intelligence for Hammacher Schlemmer’s email team that the retailer decided to extend that knowledge to the social media team.

Specifically, Hammacher Schlemmer’s email and social media teams now collaborate to develop consistent cross-channel experiences for customers, for example by building multitouch campaigns that target customers with the same message on different channels depending on their past behavior and demonstrated interests. This approach has helped Hammacher Schlemmer convert new customers and increase the efficiency of social media spend by making it easy to share intelligent audience data across channels and keep cross-channel campaigns highly coordinated.

ASICS Reduces Size Sampling, Increases Conversion and Keep Rate with Personalized Digital Experiences

Athletic retailer ASICS was founded more than 60 years ago and is a leading designer and manufacturer of running shoes, athletic footwear, apparel, and accessories. To expand their eCommerce strategy, ASICS set out “to personalize the shopping experience for consumers by finding the products that fit well” both in terms of size and style. As is the case with many retailers, “the challenge for ASICS was about fit and lack of knowledge about their products.”

OFFERING PERSONALIZATION TO IMPROVE THE CUSTOMER EXPERIENCE

ASICS turned to True Fit to help them solve the issue of personalization. They implemented True Fit’s fit recommendation technology, True Confidence™ across all brands, including Onitsuka Tiger, ASICS Tiger, and ASICS. The technology prompts shoppers to create a True Fit profile on their site within about 30 seconds. Consumers “click on a ‘Find Your True Fit’ button or link, answer a few questions like height, weight, and age and identify a favorite brand and size of an item they currently wear that fits well.” They are then served recommendations for both footwear and apparel across the site – and any other of the 250 global sites using True Fit.

THE ROI OF PERSONALIZED AND ENHANCED CUSTOMER EXPERIENCES

Since the launch of True Fit, ASICS has seen a 150% increase in conversion from product page to cart. This translates to a 7.4% conversion rate for True Fit customers versus 2.4% for non-True Fit customers.

ADDITIONAL BENEFITS TRUE FIT DELIVERED

It also allowed shoppers to confidently try new products by creating a profile; ASICS found True Fit shoppers keep 20% more of the products they try. The brand also found a reduction in size sampling anywhere from 30% to 50%, saving the retailer from losing or discounting the product and the shopper from having to return the product.

The addition of True Fit has helped ASICS make more informed decisions based on feedback received from the customer. For instance, ASICS has been able to collect data on return rates, which enabled it to update its return policy. True Fit has also helped the mobile experience for ASICS, increasing the conversion rate, and giving customers confidence in making mobile purchases.

Making Changes in Your Organization

We’re entering a new era of retail — one that will be more global, ultra-competitive, and digitally fluid than ever before — and this shift has created a new sense of urgency around digital transformation. In this era, a modern retail marketing technology stack will be required to compete effectively.

Diving deeper, positioning your organization for success requires

  • understanding the best technology investments for your brand
  • identifying how to use those solutions together in a strategic way
  • determining when and where to start making those changes.

Critically, introducing a modern retail martech stack in your organization doesn’t have to be an “all or nothing” situation. Rather, making the right investments and positioning them correctly within your organization will be a long term initiative, so while the time to get started is now, it’s important to recognize that the full change won’t happen all at once.

As you decide where to start making changes sure to consider each layer of the modern retail martech stack and how the others will build on or interact with it, how the new solutions will deliver improvements to what you already have in place, and where the biggest gaps are in your current martech stack, especially when looking at the measurement points outlined in this guide.

Wherever you decide to start building out your modern retail martech stack, the time to start making those investments is now. We are in an “innovation race” of sorts, and the companies that invest in this type of agile technology early will be best positioned to endure and even thrive in the face of whatever happens next.

Source: Bluecore