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Ecommerce product search solution


Start collecting your customers’ data right now and boost your online store sales with the best implemented Ecommerce product search



What is Ecommerce Product Search?

How much revenue does come from Guided Navigation and Product Search on e-commerce sites? For Digital Commerce sites with thousands of products, quality navigation, and search are essential elements. Depending on the industry, navigation can generate more than 60% of revenue (in fashion), search – up to 65% (in books & media), and recommendations can generate up to 8% of revenue (in home improvement). Conversion increase by just 10% from navigation & search can generate tens of millions of dollars of additional revenue

The challenge is to display highly relevant content on shopping platforms with thousands and millions of products. Quality navigation & searches minimize the amount of time for shoppers browsing through products before they find what they were looking for. One of the market standard search tools is Oracle Endeca; it gives an incredible level of flexibility to merchandisers and marketers. Provectus’ expertise goes beyond Oracle Endeca, Solr or Elastic Search. The new era in e-commerce searching is based on a user’s behavioral data. Would you like your search tool to know exactly what your shopper wants? We know how to do that!

How does behavior driven search work

On most of the e-commerce websites, web site the visitor can see content that merchandisers and marketers prepared for a specific segment users. The classical way of doing it is to set setting this up is

  • Bust and burry for products
  • Predefined landing pages splash pages, page templates and blocks or cartridges
  • Redirects
  • Ranking strategies
  • Navigation and search rules and trigger

However, does all this that mean that the visitor really finds the product that he or she is looking for? Does the e-commerce platform take into consideration individual attributes, such as my personal preferences (even if I cannot designate them), apparel and shoe sizes, age and gender, or how often I buy specific groceries? How personal are my product search results and navigation

Predictive search and navigation can take into account clickstream data, profile settings, individual parameters of user’s behavior, and apply predictive algorithm that will output high quality individual results

The Technology

Existing market standard search tools like Oracle Endeca cannot do predictive search as they were not designed for it. Some technology companies develop their own predictive product search, navigation and recommendation tools that are supposed to fully integrated as site’s core features.. In most cases this is a complicated task that requires significant development efforts and the results might not be adjusted to a specific business in the same vertical

Instead, our approach allows building predictive product search and recommendation engines on top of existing technologies – Apache Solr, Elastic Search or Spark, that allows to use a hybrid approach between manual merchandising techniques and work of predictive algorithms

How we do it

We build a Big Data backend based using Hadoop, Amazon Kinesis and other platforms. We develop machine learning algorithms that are designed specifically for your business vertical and your needs; we use Apache Mahout. We connect Big Data backend to Apache Solr, Elastic Search or Spark using Apache Storm, RabbitMQ and other tools

The indexing of data happens in near real time, the output of data happens in real time. Such an approach allows to switch between predictive and manual search results and recommendations whenever required.

The Results

In this highly competitive market, wining retailers to rise above their competitors: provide better shopping experiences, give better conditions, run more engaging marketing campaigns, are more innovative, and run operations more efficiently
We build predictive e-commerce search tools and recommendation engines that can be targeted and fine-tuned to

  • Increase sales
  • Gather actionable customer insights
  • Improve organizational efficiency
  • Apply dynamic merchandising/ranking strategies
  • Improve overall conversion in account product view & buy cycles
  • Increase margins by liquidating underperforming products with lower levels of discounts

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