Revolutionizing Kitchen & Bath Showrooms: AI's Impact on Traditional Sales Operation

Over the past decade, the Kitchen & Bath, Appliance, Lighting, and Home Renovation sectors have witnessed a remarkable transformation. Leading product manufacturing brands in these industries have crafted a seamless omnichannel experience that transcends the traditional wholesale distribution model, integrating direct-to-consumer (DTC) investments, bespoke store designs, marketing and curated online and offline experiences. These advancements, for the most part, have successfully bridged the gap between the tactile experience of in-store interactions and the convenience of digital shopping, appealing to an upscale B2C and B2B clientele.

Yet, this evolution has brought forth distinct challenges, particularly for traditional resellers and wholesalers, who historically have been slow to adapt to a changing marketplace and business environment. They encounter the harsh realities of a digital-first economy, an ecosystem where they must now rapidly adapt. Post pandemic, many operators have established online commerce to bolster their traditional brick-and-mortar businesses. However e-commerce capability alone is no longer a forward-thinking strategy but a necessary tool for survival, especially for those operating under a two-tier distribution model. Furthermore, the shift has been acute for those serving diverse customer segments (homeowners, designers, plumbers, builders and contractors) who rely on the depth of relationships and expertise that has long been the hallmark of the sales channel.

For them, the challenges are multifaceted and fall into internal and external factors:

Internal Factors (Challenges businesses can change and have control over)

· Margin pressure: Shrinking profitability amid rising operational costs, inflation, poor inventory and market competition

· Highly variable operation & customer experience: Highly manual + high turnover

· Sales Efficiency: Low conversion, Transactional & Lacks modern systems

· Capital and People intensive: Growth = More people + More location

· Slow to adopt Technology: Limited resources + Strategic Plan

· Single channel play: Primarily offline play business

External Factors (General market challenges outside direct business control)

· Supply-chain disruption: Global logistics volatility + Adaptability challenge

· Sales channel shift from offline to online: Digital migration + Customer behavior change

· Sales highly susceptible to economic cycles: Market sensitivity + Revenue fluctuation risk

· Direct competition from suppliers & platforms: Direct-to-Consumer + Platform dominance

· Aging workforce: Generational skills gap + Knowledge transfer imperative

· Customer acquisition cost increase: Marketing efficiency decline + ROI pressure

· Online business becoming more experiential with AI: Digital engagement evolution + Traditional model disruption

So, what is different today to tackle these business challenges?

What distinguishes today's approach to overcoming longstanding challenges in the home space is the rapid maturation and widespread availability of generative AI and machine learning technologies. Previously in their infancy and hard to access, these tools have become crucial in transforming traditional commerce, heralding a new era of efficiency and innovation.

This article will concentrate on AI integration in the discovery, consultation, product selection, and order phases in a typical multiline K&B showroom or consumer-facing store.

(Shown in yellow in the diagram below)

Image Courtesy of SavantSales.AI

Understanding Generative AI Through the Lens of a Sales Process

Understanding generative AI's role in transforming retail experiences is best illustrated through a scenario many are familiar - a customer's interaction with a sales consultant on home renovation or repair projects. This scenario will demonstrate how generative AI, especially Large Language Models (LLMs), diverges from conventional retail technologies like POS and CRM systems, not by replacing but by enhancing them.

Picture entering a showroom where you greeted by a seasoned consultant to help you purchase fixtures and faucets for your bathroom renovation project. She will listen, analyze your needs, and draw upon a wealth of resources & experience to propose product options that meet your design aesthetic, budget and timeline.

Generative AI mirrors this process digitally:

1. Understanding Requirements: Like a sales consultant, generative AI tools begin by gathering information. It analyzes input data (akin to customer requirements) to understand the context of a request. This step is crucial as it sets the foundation for a relevant response.

2. Applying Knowledge and Experience: Generative AI, equipped with a vast database of information, mimics the role of a consultant drawing on years of experience. It can generate responses based on patterns, knowledge, and examples it trained on, much like a consultant uses their historical interactions and design knowledge.

3. Resource Utilization: A skilled consultant uses available resources—catalogs, samples, design tools—to inform their suggestions. Similarly, generative AI leverages the extensive data it has been trained on to produce answers, tapping into a wide array of pre-existing resources within its algorithm.

4. Tailored Recommendations: Just as a consultant proposes product options tailored to the customer’s needs, generative AI generates content that is customized to the input it receives, ensuring that the output is as pertinent and personalized as possible.

5. Clear Communication: Consultant success lies in their ability to communicate effectively. Generative AI models are designed to produce clear, coherent, and contextually appropriate language, engaging in a way that is understandable and accessible to the user.

Generative AI's potential goes beyond transactional tasks, acting more like a digital consultant that enriches the customer experience with personalized, insightful interactions. However, it's crucial to note that generative AI isn't a standalone solution. Today, it requires integration with POS, CRM, and OMS systems to access customer information and complete transactions, ensuring a seamless bridge between AI's insights and the operational backbone of sales.

Generative AI: the catalyst to transform stores and showrooms operations

The role of AI in sales enablement becomes a focused beam of light rather than a sweeping searchlight. The promise of AI lies in its precision in enhancing sales capabilities and fortifying the resilience of sales operations against the multifaceted challenges discussed above. It is about equipping the sales force with tools that streamline their workflow, offer insightful data for personalized customer interactions, and ultimately drive sales in a market that is becoming increasingly sophisticated and competitive.

AI at the intersection of People + Technology + Business Process

In the pursuit of sales excellence and profitability of complex sales process, the intersection of People, Business Process, and Technology forms the crux of a transformative strategy. This triad presents a unified framework for showroom operators to elevate their sales operations in the Awareness, Consideration and Purchase phases of the purchase journey.

Image courtesy of SavantSales.AI

People + Business Process:

• Standardize Sales Performance: Implement consistent sales practices and reduce variability in customer experiences by providing the most helpful virtual assistant to sales consultants and managers trained on product catalogs, sales process, design guides, pricing strategy and inventory.

• Bridge Knowledge Gap: Address disparities in skill and knowledge within the sales teams by blending AI, institutional knowledge, and unfettered access to information to do their job. Imagine replicating your best employees as a coach to the rest of the sales, marketing, and product organizations. Better yet, businesses can start capturing rich and critical business information not found in training manuals or brochures from seasoned and experienced employees to train and deploy AI to other teammates with built-in compensation models to those sharing their knowledge.

• Deploy Predictive Models for Sales: Use AI-driven predictive analytics to anticipate purchase decision signals, sales trends, and customer needs, and to accelerate the sales cycle. Today, most businesses are equipped to report on revenue from transactions but fail to understand the "why" behind the purchase decision or what it takes to delight every customer or find more of that same profitable buyer in the future.

• KPI & Analytics (Structured & Unstructured data): Harness key performance indicators (KPIs) and data analytics from both structured sources, like POS and CRM systems, and unstructured data, including conversational and interaction records. This dual approach unlocks actionable insights for sales strategy enhancement.

People + Technology:

• Sales Co-pilot (Selection & Quoting): Implement intelligent tools that assist salespeople in product selection and quote generation, acting as a co-pilot in the sales process.

• Seamless Chat-Lead-Quote-Order: Create a fluid transition from initial customer chat interactions to lead generation, quoting, and order, seamlessly.

• Manage HVA (High Valued Activities): Employ generative AI to analyze historical data, consultant activities, open quotes, segmentation models and customer requirements to recommend follow-up action to close the sale or remain top of mind with future clients.

• On-demand Learning: Capitalize on generative AI to provide immediate response to sales and product inquires to consultants or offer personalized learning to each individual based on existing training materials and resources, product catalog, interactive learning modules, and quizzes on demand. Let AI track progress and recommend development opportunities on what matters in real-time.

Business Process + Technology:

• Monetize Chats/Customer Interactions: Use technology to transform every customer interactions, such as chats, meeting notes and memos, into opportunities for monetization and sales. In the past, extracting meaningful insights from customer interactions during crucial phases like design, product discovery, and selection was a time intensive process and not widely utilized. Now, the ability to capture and analyze conversations, including non-verbal customer reactions to products and services with minimal effort, opens new avenues for optimizing product displays and inventory strategies. In the new era of AI, authenticated first-party data will elevate the value of the reseller and distributor to manufactures and suppliers.

• Optimize Inventory/Service Levels & Product Discovery Across the Enterprise: Leverage technology to ensure optimal inventory levels, streamline service delivery, and enhance product discovery throughout the organization.

• Accelerate Associate Onboarding: Use generative AI trained on business processes, policy, systems, product catalog and other existing training manuals to fast-track the onboarding process for new sales associates based on their specific needs and expertise at scale.

• Systemize Security & Privacy: Implement systems to ensure data security and privacy are maintained in compliance with local, state, federal, and global standards at every touchpoint with customer information and proprietary business data.

AI is Not a Panacea

AI is not a panacea for all business woes, but within the sphere of sales operation, the impact will be profound. When designed diligently and implemented with care, AI is a strategic ally in the sales process that complements human expertise with machine efficiency. It also requires exceptional leadership, communication, trust, strategic partnerships, robust brand and supplier relationships, and products to reap its full benefit.

Top 5 Actionable Steps for AI Adoption Focusing on Pre-sales Activities in Showrooms

Over the past 14 months, my collaboration with AI developers and business partners in developing AI-powered tools for frontline sales consultants, store managers, and brands has yielded invaluable insights:

1. Audit Business Operations and Identify Pain Points and Opportunities: A crucial step for successful AI implementation is a deep and intimate understanding of the sales process, operational challenges, and underlying causes. The aim is to effectively utilize generative AI capabilities and integrate them seamlessly into the existing sales framework. It necessitates a broader analysis beyond traditional retail metrics like conversion rates, AOV, traffic, and revenue. Consider a detailed time study of product quotation process, analyze the reasons behind closed-lost and closed-won sales leads, evaluate customer segmentation and store traffic quality, review the associate onboarding process and their progress toward sales targets, examine the contribution of each sales associate to gross margin, etc. Engaging a mix of internal stakeholders and an external consultant with a background in AI applications within similar sectors is critical. This strategy ensures a comprehensive evaluation of AI opportunities, merging internal knowledge with external insights for a holistic view.

2. Start Small with a Pilot Project: Choose a manageable aspect of operations for the initial AI implementation, focusing on areas promising quick wins, minimal operational disruption, and scalability. Criteria for selecting a pilot project should prioritize clear, and measurable outcomes, allowing for an evaluation of AI's impact without overhauling existing systems. This step-wise approach enables a focused assessment and demonstrates the tangible benefits of AI, facilitating broader buy-in across the organization.

3. Select the Right AI Partner or Vendor: Partnering with the right AI vendor is critical, especially one that supports small-scale implementations and demonstrates a successful track record in the wholesale sector. Vetting AI vendors effectively involves evaluating their experience with businesses of similar size, seeking industry-specific case studies, and ensuring they offer comprehensive post-implementation support.

4. Invest in Training and Change Management: Generative AI will revolutionize operations and can inadvertently impact team dynamics. For instance, the traditional method of assigning new customers to sales associates based on expertise will evolve. With the AI co-pilot, a plumbing expert can confidently handle tile orders, or a kitchen cabinet specialist can advise on lighting options. This will be great for the business owner but not for incumbent professionals. Critically, the success also hinges on unwavering executive sponsorship from both the business unit and IT departments, ensuring a comprehensive support, endorsement, and ongoing refinement through exploration, model training, and back-testing.

5. Monitor, Measure, and Scale: Establishing clear KPIs to monitor the success of AI implementation allows for informed decisions about scaling AI solutions across the business.

Parting Thoughts

In an era where generative AI and machine learning are not just knocking on the door but kicking it wide open, the call to action for the Kitchen & Bath, Appliance, Lighting, and Home Renovation sectors is unequivocal and urgent. The leap to e-commerce once felt like a marathon; today, the integration of AI demands a set of 100-meter sprints.

The reluctance or delay that characterized the e-commerce or DTC adoption cannot be the narrative for AI. This technology is reshaping expectations, operations, and the very fabric of customer interactions faster than anything we've seen before. The question isn't about if you can afford to integrate AI but whether you can afford not to.

The clock isn't ticking; it's racing. Are you ready to sprint?

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Author : Felma Degefa

Contact Information : Felmadegefa@savantsalesai.com c.(610) 909 9056