It’s time to be honest as ecommerce professionals: search goes beyond search engines like Google, Bing, or DuckDuckGo– your ecommerce site is its own search engine.
Customers enter your website and start a search and discovery process. Some will navigate with a drop-down menu, others will go right to the search box, while others will see what the page they landed on offers them. How they search and discover matters to your bottom line – it’s the first step toward a conversion.
According to Forrester, 75% of US adults say it’s important for retailers to provide advanced search features, including refining results by price, brand, style, or other product attributes that are important to them.
Search and adequate filters is the top site feature customers care about. But, far too many brands and retailers haven’t invested in modernizing their digital commerce search capabilities to fit the needs and devices consumers have.
In a live conversation with Forrester’s Scott Compton, we discussed the evolution of search in e-commerce, the implications it has on business, and what brands and retailers must prioritize now to be ahead of the competition — and most importantly, be the preferred option for customers to purchase from.
5 Opportunities to Maximize Impact of Search for Better Ecommerce Experience & Performance
1. Don’t Ignore the Importance of Mobile in Omnichannel
62% of the world’s population has a smartphone and the way we use smartphones have evolved over the last few years. It’s not just browsing social networks or checking maps, it’s making purchases directly from our Instagram feed or looking up a product while in-store to make our purchase decision. The shift to using mobile search in-stores is a game-changer for cross-brand shopping and puts more pressure on the digital shelf to be a research tool in addition to a purchase channel.
Mobile search isn’t considered enough within the customer journey and it’s costing brands and retailers significantly. Mobile commerce requires more than just a responsive design-it needs to be seen as its own unique channel to be optimized. Some of the most neglected yet critical parts to consider include filters, mobile UX, and ease of navigation within menus and pages.
2. Implement Conversational Capabilities
Search results need to be localized and context-driven; this is easier with mobile as it can be highly geo-specific. Scott highlighted the value of conversational capabilities as a way to personalize the search experience right away:
Conversational search is a great way to engage with customers on mobile, you can have a 1:1 interaction to drive personalization in the first visit.
A conversational experience allows brands to service the next filter for that customer and can be used by in-store associates. Think of search as essentially the online version of your retail sales clerk in addition to being a self-guided experience where customers have the information and make a choice themselves.
3. AI Improves Operational Efficiency
The automation that comes from implementing solutions powered by AI and machine learning replaces laborious manual tasks for businesses. It’s fair to be nervous about the implications of AI, but moving away from old search to new search frees teams to drive a better experience rather than managing an outdated manual back-end that is unable to serve customer needs.
To put it simply, old search match keywords in content with the query — if you wanted to add synonyms or misspellings, that is manually done as the backend of the search platform is static and needs to be fed the information through a person.
New search capabilities are contextually driven and leverage semantic data automates that from constantly learning, evolving, and optimizing. It is able to determine intent through the context of the user, geo-location, purchase history, and even stated preferences. AI improves operational efficiency whilst allowing teams to drive more meaning from the search experience than ever before.
4. Embrace Semantic Data
Speaking of automation, search solutions with semantic data models are vital to a digital-first world. Semantics derives meaning from the query. Customers don’t speak in keywords and they shouldn’t be expected to know exactly what keyword matches their needs. Machine learning creates relationships with queries, adapts the relationship within the system, and enriches data to better understand intent.
The ability to determine intent from difficult queries and surface an accurate result creates a better search experience for your customers. With the right technology, each query can enrich existing data for continuous optimization based on real customer interaction, not just assumptions.
Data is the foundation of every successful experience: it needs to be smart, structured, clean and constantly enriched. Semantic data makes this as simple as adding the intelligence into the backend of your existing interface.
For the first time, brands and retailers have visibility to compare and contrast what products surface for a particular query, to see what visual drove the conversion, and use it to inform marketing or customer service.
5. Think Convenience Always
Convenient findability is the top priority. As touchpoints evolve, the customer decides their journey based on where they prefer to engage and its brands and retailers’ responsibility to capture them in those moments to drive a purchase or surface the right information.
When identifying opportunities to improve search across channels, but particularly from a mobile-first perspective you must put yourself in your customer’s place. How intuitive is our mobile navigation? Do we engage them in a conversation? Can we understand the context and intent of their search? How convenient do we make buying from us? should be constantly considered.
Lastly, break the mold of what search results can be: it can be a product, information, content, or the journey itself. The journey from search to conversion has evolved: has your business?