Conjunto de herramientas AI para CIO y CDO de marcas minoristas

Welcome to the definitive AI Toolkit designed for CIOs and CDOs of retail brands. This guide is your go-to resource for navigating AI adoption across sales, distribution, and business operations—whether you’re part of a rapidly scaling organization or an established enterprise.

01. AI Options: Corporate Centralised AI & SaaS Embedded AI

Retail brands have two primary AI approaches. Understanding their differences is critical for selecting the right balance for your business needs.

CriteriaCorporate Centralised AISaaS Embedded AI
Training Data SourcesMultiple systems like ERP, SFA, DMS, HRMS, E-Commerce, etc.Complete-in-itself platform (e.g., Sales, Service, Procurement)
Tiempo de despliegue12–24 months; requires complex integrations and data lake setupWeeks to months; often pre-trained and ready-to-use
Use Case ExamplesEnterprise-wide forecasting, resource allocation planningOrder recommendations, procurement risk prediction, employee engagement
IT ComplexityHigh – needs data lakes, data pipelines, robust APIs, governance, integration layersLow – minimal integration required
ScalabilityBroad scope across functions and geographies, but constrained by IT complexityQuicker scalability within specific workflows and functions
Investment LevelHigh upfront costs with long-term strategic benefitsLower cost with immediate business impact and ongoing vendor-led innovation

02. AI Adoption Strategies

2.1 Strategies for Smaller & Mid-Sized Organisations

These businesses typically lack the resources to build a centralised AI setup. Instead, they should aim for minimal overhead with maximum impact.

ChallengeSolutionDetailed Approach
Limited BudgetAdopt ready-to-deploy SaaS AIUse subscription-based unified platforms to lower Capex
Data FragmentationUse integration-friendly toolsStandardize inputs across systems; avoid full-scale data lake
IT Resource ConstraintsPrioritize embedded AIChoose pre-trained, plug-and-play tools
Tool SprawlConsolidate systemsSelect platforms scalable enough to cover a full function (sales, procurement, HR); avoid over-consolidating on horizontal tools

Note: Avoiding a full data lake and choosing point-to-point integrations creates vendor decoupling risks—but helps sidestep significant infra costs.

2.2 Strategies for Large & Mature Enterprises

For large enterprises, a hybrid AI strategy is recommended: use Embedded AI for quick wins and Centralised AI for long-term, cross-functional insights.

Key FactorRecommended StrategyDetailed ApproachExpected Outcome
Data ManagementLeverage existing infra for Embedded AI; selectively integrateUse unified platforms + high-impact centralized analyticsRapid deployment; scalable as use cases grow
Vendor Risk ManagementEnsure easy system decouplingChoose best systems per functionGreater flexibility, reduced vendor lock-in
ScalabilityHybrid approach for scalability in both function and enterprise-wide levelsStart with embedded, grow into centralizedImmediate ROI; long-term innovation
Enterprise ArchitectureUse open, modular systemsAvoid full-scale data lake unless necessaryAgile infrastructure for future growth
ConfigurabilityPrefer industry-specific, enterprise-configurable toolsAI should allow toggle, retraining, and custom flowsMore alignment with unique needs

Quote
“We have evolved from building everything in-house to only building custom use cases. For the rest, we buy best-of-breed enterprise platforms and integrate via a data orchestration layer.”
- Nischai Nevrekar, Chief, Digital Initiatives

2.3 Build vs. Buy Decision

The build vs. buy decision is especially critical in the AI era due to the pace of technological change.

Three Phases of Building In-House

MetricConstrucción propia AIBuy SaaS Embedded AI
Development CostHigh—dedicated AI team & infra neededLower—subscription-based, vendor support
Time to Deploy12–24 months (uncertain outcomes)Weeks to months—evaluate before buying
Maintenance & UpgradesOngoing, resource-intensiveVendor-managed, predictable cycles
Realización del ROISlow, uncertainFast, measurable with clear metrics

03. Justifying the AI Investment: ROI & Business Impact

A clear, structured framework is vital to justify and secure AI investments.

AI ROI Calculation Framework

Cost ComponentInvestment DetailsPotential ROI Impact
Infrastructure SetupCloud services, data lakes, AI platformsImproved data readiness; scalable insights
Software LicensingSubscription fees for AI toolsRevenue uplift via optimized sales & pricing
Operational CostsTraining, vendor fees, supportSavings from automation and lower manual work
Implementation Time3–12 monthsFaster time-to-market; better competitive edge

ROI Formula
ROI = (Aumento de ingresos + Ahorro de costes) / AI Inversión

Example
Revenue = $1000
RTM Cost = $100
AI Uplift = 5% revenue + 10% cost reduction
AI Inversión = $10
ROI = ($50 + $10) / $10 = 6X

04. Building an AI-Ready Team for Retail and Consumer Goods

Your team determines the success of your AI initiatives. Focus on integration, strategy, and measurement—not just development.

Best Practices

  • Prioritize mature, pre-trained AI solutions over custom development.
  • Equip your team to evaluate AI vendors.
  • Build capabilities for impact measurement—every leader will demand it.
  • AI security can be in-house or outsourced.

Essential Roles & Responsibilities

RoleKey ResponsibilitiesFocus Areas
AI StrategyDevelop AI roadmap; align with goalsStrategy, ROI, vision
AI Vendor ManagementEvaluate/select vendors; ensure fitVendor selection, contracts, performance
AI Data AnalysisMeasure outcomes; track KPIsData quality, continuous improvement
IT AI IntegrationSeamlessly embed AI into systemsSystems integration, support, governance

05. About BeatRoute & Our Approach to AI

BeatRoute is a goal-driven SaaS platform serving 200+ enterprise brands in 20+ countries. Our platform is scalable, configurable, and designed to deliver measurable sales impact across retail sales and distribution networks.

What Sets BeatRoute Apart

  1. Goal-Driven AI: Ready-to-use AI with easy integration options for centralized intelligence.
  2. Highly Configurable: Adapt to your processes and workflows.
  3. Continuous Learning: AI improves as it learns from your data.

Sales Uplift from BeatRoute’s Goal-Driven AI

Use CaseUpliftModules & WorkflowsMeasurement Parameters
Sales Team Enablement12.6%KPI Scorecard, Operational AI (Help Me Plan, Task Recommendations), Gamification, Conversational AIMonthly sales pre/post, lines sold, new retailer ratio, gamification leaderboard movement
Customer Engagement5.2%Milestone visibility, Spin & Win, Communication campaigns, Order Nudges, Customer GamificationSales pre/post, lines sold, scheme budget use, incremental orders
Operational AI4.3%Order Recommendation AI, Help Me Plan, Task Recommendations, Customer InsightsMonthly sales, productive visit count, average order value
Conversational AI & Analytics5.3%CuesBot, Configurable Dashboards, Competitor InsightsSuggested vs. actual actions, manager actions pre/post, sales from same set of customers

Ready to Build a Long Term AI Stack?

Book a free demo with BeatRoute to see our AI in action, and learn how you can incorporate our AI platform in your tech stack.

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