What are our data sources?
We use the data sources on the side for ranking solutions and awarding badges in retail, proximity & iot marketing tool category. Our data sources in retail, proximity & iot marketing tool category include;
Proximity marketing is location-based marketing that involves using customers’ location to market products and services. It utilizes location data provided by smartphones or Internet of Things (IoT) devices and helps businesses to deliver more relevant ads. By using proximity marketing tools, retailers can reach the right audience at the right time when they are at the right location.
If you’d like to learn about the ecosystem consisting of Retail, Proximity & IoT Marketing Tool and others, feel free to check AIMultiple IoT.
AIMultiple is data driven. Evaluate 141 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.
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We use the data sources on the side for ranking solutions and awarding badges in retail, proximity & iot marketing tool category. Our data sources in retail, proximity & iot marketing tool category include;
review websites
social media websites
search engine data for branded queries
According to the weighted combination of 7 data sources
Epicor Prophet 21
Oracle NetSuite API
Infor Dynamic Enterprise Performance Management
Lightspeed POS
Vend
Taking into account the latest metrics outlined below, these are the current retail, proximity & iot marketing tool market leaders. Market leaders are not the overall leaders since market leadership doesn’t take into account growth rate.
Epicor Prophet 21
Oracle NetSuite API
Lightspeed POS
Infor Dynamic Enterprise Performance Management
Vend
These are the number of queries on search engines which include the brand name of the solution. Compared to other IoT categories, Retail, Proximity & IoT Marketing Tool is more concentrated in terms of top 3 companies’ share of search queries. Top 3 companies receive 80%, 2% more than the average of search queries in this area.
43 employees work for a typical company in this solution category which is 22 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. 61 companies with >10 employees are offering retail, proximity & iot marketing tool. Top 3 products are developed by companies with a total of 500k employees. The largest company building retail, proximity & iot marketing tool is EdgeVerve Systems with more than 300,000 employees.
Taking into account the latest metrics outlined below, these are the fastest growing solutions:
Epicor Prophet 21
Oracle NetSuite API
Infor Dynamic Enterprise Performance Management
Lightspeed POS
Vend
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 Retail, Proximity & IoT Marketing Tool companies. The most positive word describing Retail, Proximity & IoT Marketing Tool is “Easy to use” that is used in 8% of the reviews. The most negative one is “Difficult” with which is used in 2.00% of all the Retail, Proximity & IoT Marketing Tool reviews.
According to customer reviews, most common company size for retail, proximity & iot marketing tool customers is 1-50 Employees. Customers with 1-50 Employees make up 39% of retail, proximity & iot marketing tool customers. For an average IoT solution, customers with 1-50 Employees make up 18% of total customers.
These scores are the average scores collected from customer reviews for all Retail, Proximity & IoT Marketing Tools. Retail, Proximity & IoT Marketing Tools is most positively evaluated in terms of "Overall" but falls behind in "Likelihood to Recommend".