What are our data sources?
We use the data sources on the side for ranking solutions and awarding badges in e-commerce personalization software category. Our data sources in e-commerce personalization software category include;
E-commerce personalization software collects user data through different channels. These tools deliver personalized messages and recommend products based on user behavior and purchase history.
If you’d like to learn about the ecosystem consisting of E-Commerce Personalization Software and others, feel free to check AIMultiple E-Commerce.
AIMultiple is data driven. Evaluate 124 services based on
comprehensive, transparent and objective AIMultiple scores.
For any of our scores, click the information icon to learn how it is
calculated based on objective data.
*Products with visit website buttons are sponsored
Optimizely is the world's leading experimentation platform, empowering marketing and product teams to test, learn and deploy winning digital experiences
Bloomreach offers an open, java CMS and an AI-powered search and merchandising solution designed for businesses to boost conversions
We use the data sources on the side for ranking solutions and awarding badges in e-commerce personalization software category. Our data sources in e-commerce personalization software category include;
review websites
social media websites
search engine data for branded queries
According to the weighted combination of 7 data sources
ActiveCampaign
Optimizely
BloomReach
Algolia
Moosend
Taking into account the latest metrics outlined below, these are the current e-commerce personalization software market leaders. Market leaders are not the overall leaders since market leadership doesn’t take into account growth rate.
ActiveCampaign
Optimizely
Moosend
BloomReach
Algolia
These are the number of queries on search engines which include the brand name of the solution. Compared to other E-Commerce categories, E-Commerce Personalization Software is more concentrated in terms of top 3 companies’ share of search queries. Top 3 companies receive 41%, 32% more than the average of search queries in this area.
384 employees work for a typical company in this solution category which is 363 more than the number of employees for a typical company in the average solution category.
In most cases, companies need at least 10 employees to serve other businesses with a proven tech product or service. 74 companies with >10 employees are offering e-commerce personalization software. Top 3 products are developed by companies with a total of 10k employees. The largest company building e-commerce personalization software is [24]7.ai with more than 8,000 employees.
Taking into account the latest metrics outlined below, these are the fastest growing solutions:
ActiveCampaign
Optimizely
BloomReach
Algolia
Yieldify Conversion Platform
We have analyzed reviews published in the last months. These were published in 4 review platforms as well as vendor websites where the vendor had provided a testimonial from a client whom we could connect to a real person.
These solutions have the best combination of high ratings from reviews and number of reviews when we take into account all their recent reviews.
This data is collected from customer reviews for all E-Commerce Personalization Software companies. The most positive word describing E-Commerce Personalization Software is “Easy to use” that is used in 9% of the reviews. The most negative one is “Difficult” with which is used in 2.00% of all the E-Commerce Personalization Software reviews.
According to customer reviews, most common company size for e-commerce personalization software customers is 1-50 Employees. Customers with 1-50 Employees make up 70% of e-commerce personalization software customers. For an average E-Commerce solution, customers with 1-50 Employees make up 57% of total customers.
These scores are the average scores collected from customer reviews for all E-Commerce Personalization Software. E-Commerce Personalization Software is most positively evaluated in terms of "Overall" but falls behind in "Likelihood to Recommend".
This category was searched on average for 125 times per month on search engines in 2022. This number has decreased to 70 in 2023. If we compare with other e-commerce solutions, a typical solution was searched 309 times in 2022 and this increased to 320 in 2023.