ISG Provider Lens™ Specialty Analytics Services - Retail - Global 2024

Retailers choose specialty analytics providers for tailored solutions and differentiation

Retail analytics for differentiation

As competitive differentiation narrows, retailers scramble toward harnessing their data assets to offer improved and personalized customer interactions and stay ahead in the race. However, traditional retail analytics cannot fulfill this completely, and over-the-shelf products promise little to no differentiation. Hence, to thrive, retailers apply their understanding of challenges and business acumen to codevelop tailored AIbased analytics solutions with leading analytics providers to infuse the needed flexibility and ensure rapid responsiveness into their  planning, execution and customer processes.

Many leading brick-and-mortar retailers are also foraying into e-commerce, which is now creating an entirely new stream of customer behavior data that retailers can use to create value. This data explosion is further enriched with market intelligence data that allows retailers to create highly accurate customer profiles and act according to their preferences. This also enables retailers to opt for the most relevant marketing-mix model with tailored pricing and promotions that significantly enhance the return on their marketing expenses.

While striving for differentiated customer experiences and marketing analytics, retailers cannot neglect their core processes related to merchandising, supply chain and store operations, especially when the past four years have only exposed the fragilities of supply chains worldwide. Any disruption in operations could mean substantial financial losses and client attrition. Retail analytics helps retailers adapt to changing tech environments by leveraging AI and ML models with simulation capabilities. This helps retailers predict the
market demand and take preemptive actions for effective inventory assortment to avoid stockouts and enhance visibility around logistics, distribution and store-level activities. Hence, ISG expects these to be the next focus areas for retailers over the next few years.

Navigating the data hurdles faced by retailers

In this context, while adopting analytics to solve business problems may sound logical and intuitive, retail enterprises have their own challenges that discourage them from investing in analytics. Some of the key challenges retail enterprises face with analytics initiatives and road maps include:

• Integrating data from diverse sources to create a robust data foundation for digital transformation, which requires data harmonization across disparate systems and formats.

• Proving tangible ROI from past analytics investments to ensure continued leadership support for incremental resource allocation. This needs volumetric and experiential metrics and success stories to demonstrate value generated from previous initiatives.

• Scaling siloed analytics and AI implementations across entire enterprises to maximize their impact on various value chain areas requires clear governance structures, interoperable systems and collaboration
among business and IT teams.

• Addressing the limited flexibility inherent in prepackaged solutions and their nature of nontransferrable intellectual property (IP), which prevents any customization to meet unique business requirements. Hence,
organizations must undergo thorough deliberation on using products versus adopting tailored solutions.

Hence, every retailer, big or small, will need to develop the capability to be data driven in its execution. However, the limited flexibility inherent in prepackaged software products prevents retail enterprises from customizing them to tackle their unique business challenges. The nontransferrable intellectual property also poses significant deterrence in attaining competitive advantage in an industry that thrives on  hyperpersonalization of customer interactions and just-in-time (JIT) strategies for inventory planning and cost optimization. Therefore, many retailers globally are now looking for specialized analytics providers for agile solutions tailored to evolving consumption patterns, macroeconomic conditions and even geopolitical tensions.

Specialty analytics providers are driving the retail innovation

Specialty analytics providers prioritize domain expertise when designing and delivering analytics solutions for retailers. These providers have services portfolios that include consulting, design, development, deployment and managed services, primarily across multiple industries. A typical engagement model comprises the
following steps:

• Client maturity assessment: Service providers evaluate the maturity of clients’ analytics capabilities, create tailored road maps and align solutions with client objectives to deliver intelligent processes and differentiated experiences.

• Robust data foundation: Most service providers have a data ingestion platform or accelerator to create the data pipelines required to activate analytics applications.

• Business problem solving: This step includes applying accelerators and pre-built AI and ML models for the most common retail scenarios. The most mature areas include customer and marketing analytics.

However, significant improvements have been made to the core retail process over the last 2 - 3 years.

• Creation of custom solutions and open IP: Service providers use retail-specific prebuilt AI and ML models to develop tailored solutions for various use cases and typically follow an open IP approach, where the client remains the solution IP owner.

• Pricing models: Retailers are usually billed on a combination of time and material (T&M) and fixed-cost basis. ISG has observed some projects that follow outcome-based pricing.

The analytics services provider market is crowded with companies of extreme scales and capabilities, from multinational IT services companies to consulting firms. However, specialty providers are effectively carving out their niche by implementing the following strategies:

• Investments in technology and data partnerships: A significant share of revenue is invested in R&D, forging strategic partnerships in technology and vertical-specific data and launching initiatives to enhance data and technology capabilities in retail analytics.

• IP assets in the form of retail solutions and accelerators: Service providers develop proprietary platforms, accelerators and retail-centric use case solutions to address specific business needs and accelerate time to market for clients.

• Ability to customize and custom development: Service providers offer customization and custom development services to tailor solutions to client’s unique requirements and industry-specific challenges by leveraging their industry experience and domain experts.

GenAI is changing the way retailers interact with data

The rapid development of generative AI (GenAI) use cases in centers of excellence (CoEs) and retailers’ high number of proofs of concept (PoCs) indicate this technology’s potential to create additional business value.
While most use cases are still employee facing and focused on process efficiency, ISG observed several customer-facing GenAI initiatives getting deployed and generating measurable value for the clients. These use cases employ various technologies, including natural language processing (NLP), computer vision and proprietary and open source large language models (LLMs) to solve complex business problems.

As GenAI’s significance extends beyond isolated use cases, it emphasizes a holistic approach that includes consulting, design, development, deployment and managed services to maximize its potential, helping clients achieve optimal results. Retailers seek service providers capable of integrating expertise from various disciplines, including data science, machine learning, engineering, design thinking, domain knowledge and user experience design, to optimize business functions for competitive advantage.

Embracing ESG, responsible AI and compliance

Emerging themes in retail analytics include a focus on environmental, social and governance (ESG) factors, and the adoption of ethical AI practices to ensure fairness and transparency in decision-making processes. The providers feature ESG-related developments prominently in their road maps as regulators around the
world become more stringent on ESG reporting and retailers actively look to curb their carbon emissions.

The providers protect client data by implementing robust data management policies and architectures that are compliant with relevant regulations such as GDPR, Health Insurance Portability and Accountability Act
(HIPAA) and California Consumer Privacy Act (CCPA). Further, authentication processes, role-based access controls and encryption, masking and anonymization techniques ensure data security at all levels.

In summary, retailers can move away from off-the-shelf retail software and partner with specialty analytics providers that offer critical domain expertise and flexibility to codevelop bespoke solutions, effectively addressing unique and complex operational challenges.

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