A significant hurdle awaits eCommerce small and medium-sized businesses (SMBs) venturing into the realm of artificial intelligence (AI) implementation. The prevalent challenge lies in the lack of connectivity among their systems, resulting in a fragmented data landscape. SMBs are faced with the daunting task of establishing connections between multiple systems, a time-consuming endeavor that proves arduous for businesses with limited resources. Statistics from Salesforce’s research report highlight the need for immediate action, as the average SMB operates on average 4-7 SaaS systems, leading to wastage of both time and money.(1)
Mikel Lindsaar, CEO of StoreConnect, says the flaw in the terminology itself highlights the disconnect between perception and reality. “AI, as it exists today, primarily operates on machine learning principles, rather than true intelligence,” Lindsaar explains. “It functions by predicting responses based on the data it has been trained on. However, if flawed or incomplete data is fed into the system, it will generate inaccurate predictions. Small eCommerce businesses, already burdened with numerous disparate apps, find it nearly impossible to integrate accurate and comprehensive data into AI systems.”
AI technologies, previously dominant in large global companies, are now making their way downstream to SMBs, becoming increasingly accessible to smaller businesses. As AI technology becomes more accessible to small and medium-sized businesses, challenges arise including budget constraints, justifying expenses, implementation difficulties, limited time for employee training, and scalability concerns as businesses grow.
Strategies for SMBs to Embrace AI
To address these critical challenges, Lindsaar claims SMBs must take the initiative to streamline their operations. By organizing their data within a unified platform, they can leverage the AI capabilities embedded in enterprise-level solutions. Enterprise platforms provide a centralized hub where all data is consolidated, enabling small businesses to benefit from sophisticated AI algorithms despite their limited dataset.
The efficacy of AI hinges on the availability of extensive and diverse datasets for training. Large enterprises with access to vast amounts of data have been at the forefront of AI adoption due to their ability to ingest substantial volumes of information. In contrast, SMBs grapple with the limitations of their smaller datasets, hindering their AI capabilities and limiting potential growth opportunities.
Leading players in the industry, including prominent e-commerce platforms, are now utilizing AI to predict customer behavior and enhance the shopping experience. By offering tailored product recommendations based on machine learning models, these platforms empower businesses to optimize sales opportunities. To access such benefits, small businesses must align themselves with platforms that already possess extensive data resources, allowing them to harness the power of AI and drive business expansion.
The Caveat of Enterprise Platforms
But building a business solely on e-commerce or marketplace platforms like Shopify or Amazon poses inherent risks. Small businesses find themselves at the mercy of these platforms, with limited ownership of customer data. Additionally, the complexity of managing various systems outside the e-commerce domain hampers scalability. Attempting to integrate AI across multiple systems simultaneously becomes an insurmountable challenge, plunging businesses into the abyss of “SaaS hell and plugin purgatory.”
StoreConnect, built on the robust foundation of the world’s #1 CRM, offers a solution to this predicament. By consolidating all data within one enterprise platform, businesses gain access to a comprehensive overview of their operations. This holistic approach facilitates better marketing and sales strategies, inventory management, and data-driven decision-making. Embracing a single source of truth empowers small businesses to thrive in the AI revolution and surpass their growth ceilings.
The time to act is now. Small businesses must avoid complacency and proactively create their business framework around one master data management (MDM). Failing to do so risks being left behind as competitors harness the full potential of AI-enabled insights.
Additional AI Obstacles for SMBs
In addition to the issues of integration with existing systems and scalability, Lindsaar says implementing AI poses additional several challenges for SMBs, including:
1. Lack of expertise: Finding and retaining skilled AI professionals can be difficult for SMBs.
2. Data quality and availability: Ensuring clean, relevant, and sufficient data for AI training can be a hurdle.
3. Ethical considerations: SMBs must address data privacy, security, and algorithmic biases.
4. Change management: Adoption of AI requires managing workflow changes and employee acceptance.
5. Regulatory compliance: SMBs must navigate AI-related regulations and standards.
The benefits of transitioning to a unified platform are immense for SMBs, Lindsaar says. Not only do businesses free up valuable resources by automating inter-system communication and reduce the need for multiple SaaS apps, but they also enable their marketing and sales teams to focus on revenue-generating activities. With AI’s analytical prowess, small eCommerce businesses can capitalize on precise and targeted marketing strategies, leading to substantial revenue growth. Embracing the efficiency gains and unlocking the full potential of AI through a single source of truth holds the key to explosive growth for small businesses.
By being able to capitalize on enterprise capabilities and large data sets, SMBs can benefit from the AI revolution. And by using solutions that eliminate the need for repetitive data entry, SMBs can focus their time and efforts on core operations, leading to improved efficiency and productivity.
