Artificial intelligence (AI) is changing the way brands interact with buyers. According to recent survey data from McKinsey & Company, business leaders are now using generative AI (GenAI) to help them better understand customers and deliver personalized experiences.
Intelligent tools are also changing the way buyers interact with brands.
As noted by research firm Gartner, total search engine volume will drop 25% by 2026 as customers turn to AI chatbots and virtual agents to help find best-fit products and services.
For ecommerce brands, the move to intelligent solutions requires more than just technology adoption. To make the most of AI, companies need an implementation roadmap that helps them find, deploy, and manage new tools effectively.
Not sure where to get started? Here’s a seven-step plan to effectively integrate and apply AI.
Before diving into what steps you can take to improve AI's impact, let’s talk about why these steps are necessary.
Generative AI tools have fundamentally altered how consumers interact with the digital world. While first-generation chatbots could answer simple questions and provide stock answers, emerging tools can handle complex queries, understand emotional context, and provide personalized responses.
This makes it possible for buyers to streamline the discovery and evaluation of potential products. Instead of using search engines to query popular terms and then wade through a mix of sponsored and authentic results, customers can simply ask chatbots or purpose-built AI agents to create a curated list of personalized recommendations.
While search engines will still play a role in purchasing decisions — for example, the rise of generative engine optimization (GEO) alongside traditional search engine optimization (SEO) is a critical component in effective marketing — ecommerce brands can’t afford to ignore the impact of purpose-built AI tools.
To make the most of AI, planning is paramount. Here are seven steps to help kickstart AI adoption.
First, evaluate current sales and marketing operations to see what’s working, what isn’t, and where you need to improve.
Consider an ecommerce brand that sells fashion and apparel products. As more competitors move into this space, the company’s sales and customer volumes are falling. SEO analysis reveals a drop in organic and ad-driven search traffic. Further research reveals that leading brands feature robust, AI-driven recommendation and customization tools that help remove uncertainty from the buying process.
Infrastructure readiness also plays a critical role. This is because AI tools are resource-intensive — more complex algorithms handling larger data volumes require more processing power, which can put a strain on current resources. Before adopting AI, it’s worth making sure that your current infrastructure can handle the demand.
What sets AI tools apart from traditional digital solutions is their ability to learn over time. Using a combination of large-scale datasets and machine learning (ML) algorithms, intelligent tools can deliver more accurate and relevant answers.
The rapidly evolving nature of AI, however, means that there’s no “standard” solution. For example, some brands choose cloud-based AI to help offload resource requirements, while others opt for AI-enabled devices capable of handling complex compute processes on-site.
For some companies, it makes sense to spend on simple AI tools that obtain basic customer data and then escalate interactions to human staff. For others, fully automated tools are the best way to move prospective purchasers down the sales funnel.
AI is powerful but not without pitfalls. Consider recent data from Statista, which found that just 9% of American consumers felt AI made the online shopping experience better. In fact, 14% said AI made the experience worse, 2% said it was “almost the same,” and 56% said how AI was used made all the difference.
To avoid possible pitfalls, identify key business goals and then assess potential roadblocks. For example, if you want to build an AI assistant that provides personalized product recommendations for customers, make sure the solution can take them directly to product pages — and make sure these pages contain complete, accurate, and up-to-date information.
Put simply: You need to start and finish strong for success. If AI can’t offer personalized suggestions, you’ll lose customers at the first hurdle. If tools don’t point the way to in-depth product pages, you could lose them at the last moment.
Next up is implementation. While many new tools easily interface with current solutions ecommerce brands need to pick a starting point for AI deployments, then decide how and when to scale up these solutions.
Users form the cornerstone of your deployment strategy. If customers and staff find these tools cumbersome or confusing, they won’t deliver ROI. From an employee perspective, education is critical. Keep staff in the loop about upcoming AI deployments, and give them the chance to experiment with AI solutions before they’re deployed. On the customer side, always provide an option for assistance to reduce the risk of customer churn.
AI is only as good as its performance. For example, if virtual assistants are driving increased sales, it may be worth expanding their scope. If conversion numbers aren’t moving, businesses may need to reassess their deployments.
Measurements and metrics make it possible for brands to quantify AI impacts. For example, you might track the number of new customers in the four months after AI deployment and compare it to the four months prior. You might choose to monitor overall sales numbers, average purchase total, or even customer satisfaction scores.
The more you know, the better your AI.
The core of AI solutions is continuous learning — but this doesn’t mean tools are fire-and-forget. Instead, ecommerce brands need to regularly evaluate current performance against expected outcomes.
If tools are underperforming, seek out user feedback for insight. If solutions are working as intended, consider scaling up deployments. And if frameworks exceed expectations, leverage collected data to help you better understand your target audience.
The final step is short and simple: Always keep a human in the loop. This could mean designating a team to review all AI decisions or assigning staff members to review any AI alerts about duplicate information or data quality issues.
Think of AI as a remarkably gifted child. Sure, there’s massive potential, but experience is lacking. Regular check-ins help keep projects on track.
While the extent of AI impact remains uncertain, there’s no question that intelligent tools are changing the way ecommerce companies capture consumer interest and drive sales conversions.
The result? Your business needs to stay the course on AI — whatever that course looks like for your brand. Start with this seven-step plan to build a framework that aligns with your marketing goals, enables your sales strategy, and keeps customers coming back.