Retail Analytics Research Report
Retail operations, and the broader retail landscape, have transformed over the last decade. Highlighted by the digitization of the shopping experience, increased customer personalization and diversification of in-store operations, brand and retailer adoption of technology is accelerating. Many customer touch points exist along the “path to purchase” and each junction presents an opportunity to implement technology to both streamline the buying process and collect valuable information that can be used to further optimize operations. We define Retail Analytics as the technology that brands, and retailers leverage to increase the likelihood of an initial and repeat purchase. From traditional POS systems and store management software to location-based beacon technology, there are dozens of solutions to help increase average order value (e.g., suggesting additional items) or capture an extra percentage point on customer conversion. Retail Analytics solutions improve the customer experience, increase brand equity, streamline in-store operations and ultimately drive sales and reduce costs for retailers.
As we shop around the Retail Analytics ecosystem, we remain focused on B2B and B2B2C software and tech-enabled businesses. We would be remiss to not acknowledge the success of e-commerce enablers and marketplaces (Shopify and Amazon), but this report takes a narrower focus on business applications serving retailers (excluding grocery) with both a physical and online presence. Furthermore, we investigate a few types of “leading edge” solutions that are leveraging newer technologies to further engage customers and create a unique shopping experience. This deep-dive into the Retail Analytics landscape outlines our analysis of the market size, our thesis regarding the functionality of, and interactions amongst, various players and ultimately aims to serve as a guidepost for the industry’s maturity.
Before jumping on the “brick and mortar retail is dead” or “no one can compete with Amazon” bandwagons, let’s first stop to level set and take an inventory of the current retail market. A recent study conducted by IHL Group indicates that there was a net increase of 4,000 stores in 2017, and over 5,000 projected for 2018. Additionally, there is a 2.7x ratio of store openings to closings.Furthermore, consumer spend is increasing, but with different preference. The chart breaks down the net ~4,000 openings and where consumers are focused:
Not to say that certain brands aren’t suffering as the online experience becomes more prevalent; however, online accounted for less than 10% of all U.S. retail sales in 2017 (17% by 2022).
Brands that can adopt and integrate Retail Analytics solutions will thrive as customers are continuously incentivized by more personalized experiences to shop in-store, but retain the ability to shop online, as well. Thus, the marriage of online and in-store operations across all functional business areas (inventory, operations, supply chain and sales and marketing) is key to competing in a digital environment. Forrester reports that top priorities among digital business strategy professionals are personalization, omnichannel, analytics and digital in-store technologies.We expect overall IT, and software in particular, spend to increase across organizations and believe that platforms capable of integrating point solutions through mobile and API integrations will ultimately gain disproportionate market share, relative to competitors.
MarketsandMarkets estimates the global Retail Analytics market to grow at a 19.7% CAGR from $3.5BN in 2017 to $8.6BN in 2022.It remains no surprise that the Retail Analytics market is approaching the $10BN mark as global retail sales surpass well over $20TN annually. However, to fully appreciate the investment that retailers are making in technology, we took a deeper look at the underlying initiatives driving this spend and confirmed with our own analysis, illustrated below:
Target Customer Overview
Target customers can be bifurcated into the following groups:
- Large, traditional retailers selling both direct to consumer and through wholesale / third-party channels
- Customers: Macy’s, Nike, Hugo Boss
- Focus: As retail becomes more customer-centric, large corporations must innovate to deliver the type of in-store and online experiences that consumers demand; they are focused on creating digital shopping experiences (web & mobile) and improving the in-store experience by leveraging store-associate tools and integrated POS systems to create a seamless experience; innovations in inventory tracking and supply-chain (RFID) remain meaningful considerations
- Contemporary, digital-centric brands with a strong online presence, also moving into brick and mortar
- Customers: Bonobos, Away, Lululemon
- Focus: Direct to consumer, digital-first brands that ‘own the customer’ are focused on strong CRM systems, marketing tools and customer analytics that can marry the online and in-store experience; as businesses scale and deliver larger volumes, sophisticated ERP and supply-chain / inventory tools become relevant to keep pace with consumer demand and ensure quality
The accompanying market map segments the Retail Analytics ecosystem into three key groups:
- Online and In-store Management – These companies encompass integrated POS systems that facilitate check-out and payment and link into other business systems such as inventory trackers, customer databases and sales analytics engines
- Tulip–Tulip Retail is a store management system offering a check-out platform that also acts an integration hub for store associates; additional features include e-commerce enablement, data management, clienteling and assisted selling; customers include Bonobos, Coach and Tory Burch
- Business Function Specific Software – Solutions in this segment cover back-end supply-chain management / inventory tracking, in-store customer experience (sales associate apps) and pure-play retail analytics
- RetailNext–RetailNext is a pure-play retail analytics solution covering loss prevention, in-store marketing, merchandising and operations; sophisticated data acquisition through various channels (smartphone, WiFi, POS) enable stores to have dashboard views of store operations; customers include the Atlanta Hawks, YETI and Club Monaco
- “Leading Edge” Solutions – Includes high-tech solutions such as AR / VR fitting rooms, interactive digital signage and location-based customer tracking systems
- Euclid–Euclid is a customer data engine capable of merging visitor information (email, mobile ID, demographics) with offline behavior (frequency, time, location) and delivering actionable intelligence; customers include malls, venues / arenas and independent retailers
This approach allows us to evaluate full-suite, holistic store management solutions as well as targeted, mission critical solutions that create stronger, more consistent brands. Despite early adoption of digitized POS systems, store management suites and online storefronts, we believe the Retail Analytics market still has a long runway for growth and has yet to reach peak maturity, detailed in the timeline below:
As previously referenced, we also evaluate Retail Analytics solutions in the context of their placement along the “path to purchase.” The following diagram outlines the breadth of Retail Analytics solutions that exist along the “path to purchase” and can be used to identify the customer impact of each technology. We view the first step in the cycle as the customer’s encounter with the product (in-store, online, marketplace, reseller or advertisement). There is then a period of consideration and evaluation, during which the customer will consult the sales associates or do independent research comparing other retailer’s products and prices. The cycle ends with a purchase, assuming the product is available and easily acquired. Ultimately, retailers capture customer information, with the hope there will be a repeat purchase (enabled through re-targeting and strong customer relations).
Pulse of the Market
We spoke with market experts to understand how leaders in the space are leveraging Retail Analytics solutions and to assess the priorities of various strategies. We believe that having a real-time view into what brands are spending the most on will help to inform our investment thesis and guide us toward specific areas for potential growth. The following recaps a portion of our findings:
- Growth Marketing and E-Commerce Executive at a Direct-to-Consumer Brand
- Top Priority:Spending on Retail Analytics across the board but marketing and advertising technology remain priorities for a digital-first brand
- Recent Initiatives:As more brick and mortar outposts are established, customer experience and tracking the customer journey will be an area of focus
- Solutions Used:Best-of-breed solutions that can address specific problems such as processing large amounts of customer data to increase marketing efficiency and sales volume; not running many pilots (cost focused)
- Key Takeaways:Focus on the customer and being a digital-first, direct-to-consumer brand allows ownership of data, leading to higher repeat purchases and customer LTV
- Former Product Manager of Retail Technology at a Direct-to-Consumer Brand
- Top Priority:Building relationships with customers and knowing their purchasing habits and specific attributes enables more targeted sales and leads to the highest ROI
- Recent Initiatives:Implementation of a true ERP system that can track products from the factory to the customer and back led to improved business ops company-wide and a CRM for clienteling allows store associate to track customers in smarter ways
- Solutions Used:ERP, prescriptive and personalization analytics engines (clienteling tools)
- Key Takeaways:Point solutions “get the job done” in the early years but company-wide ERP systems are necessary to build global operations and customer-centric tools to train repeat purchasers are necessary to compete in the digital age
- Vice President of Merchandising Strategy & Operations at a Clothing Retailer
- Top Priority:Realizing ROI on purchased solutions – marketing typically has the largest near-term ROI, followed by an increased focus on store associate applications as they enable real-time insight into buying patterns and customer preference
- Recent Initiatives:Evaluating many solutions in merchandising, planning and allocation – sees an opportunity to invest in “large technologies”, not just disruptive tech
- Solutions Used:Established an internal analytics council (led by the CIO) that drives initiatives mostly around assortment analytics (i.e., fulfillment and logistics) and visual merchandising
- Key Takeaways:Market is crowded; still a decent amount of “noise” in the market – evaluating 30+ solutions per month, 2 of which may get implemented
- Former Global Operations Strategy Director at a Global Retailer
- Top Priority:“Get the customer what they want, when they want it” – hyper-focused on inventory and supply chain (tackling these is a “logistical nightmare”)
- Recent Initiatives:Investing heavily in CRM software, trying to know the customer across their multiple distribution outlets (don’t always “own” the customer)
- Solutions Used:Investing in RFID at the supply chain level and utilizing large CRM systems
- Key Takeaways:Solutions must be implemented from the get-go to avoid chaos as the business scales – it is very difficult to retrofit solutions and track down customer data after the fact
The space is still going through somewhat early disruption and therefore has received a large amount of VC funding (up from ~$3BN in 2011 to ~$9BN in 2016, representing a 21% CAGR), but growth capital and consolidation are still to come. Despite the crowded nature of the space, we believe there are opportunities to take a position within the Retail Analytics market. We prioritize sticky, mission critical tools over feature rich / low ROI solutions. We believe that our experience evaluating vertically focused software solutions will allow us to discern which companies will achieve higher LTV from their customers. Integrated store management systems, inventory / supply chain suites and pure-play customer and business analytics engines are among the most attractive assets, from our perspective.Furthermore, cloud-first solutions that are operating on mobile, as well as the web, that have API capabilities will receive a premium.