Statistical sample of 40.000+ structures in Italy for a total of 10 Mln reviews and 4 Mln reviewers
Interprets the comments left by the users and identifies the positive/negative opinions (Sentiment)
Evaluates your on-line score on the web across time and compares it with that of your main competitors
No installation. Automatic upgrades . Multi-platform (smartphone, tablet, computer)
The reviews, constantly anlysed, make reference to structures operating in the following market fields:
UrbiStat, leader company in Geomarketing research, complementing its own services retail real estate sector, has created and developed the innovative platform Monitora, a web application for the analysis of online reviews. Thanks to the experience acquired over time through relations with large realities and to technological and statistical skills, Monitora makes use of sophisticated algorithms in order to show accurate, updated and easy-to-interpret data.
Every day, we say – How can we keep this customer happy? How can we get ahead in innovation by doing this because if we don't, somebody else will. (Bill Gates)
It is indisputable that online reviews are acquiring an increasing importance in the purchase decisional process. The spread of mobile devices and the availability of information allow people to be informed in advance and influence their purchase choices. This is the reason why every supply chain should pay attention to the reviews left by the users after they visited the point of sale/physical store.
Analysing the reviews individually may lead to misleading results: good opinions about a specific topic may result poor when all the competitors get excellent reviews about the same topic. Moreover, a comparative analysis at national level with the main competitors highlights aspects which otherwise would hardly be visible.
Score analysis (average score) in trend and of the % of satisfied customers with reference to a point of sale, a brand or a market category with the chance to insert benchmaarks, to define time intervals and/or geographic areas and to segment according to sex.
POSITIONING & TRENDS – Customized creation of line graphs, area graphs, scatter graphs by using all the analyses and the filters present in the platform.
BEHAVIOR Analysis – It allows to analyse the number of customers/users which have modified their review (making it better or worse), measures how often the owner answers to the reviews and offers an estimate of the traffic within the strucutre/shop for time of the day and day of the week.
It enables to calculate the % of male and female, to identify in which hours/days the highest number of reviews are concentrated and to define the % of customers/users shared with other structures (ex. competitors) comparing their opinions.
It allows to generate comparison matrices between different structures or point of sales of a chain on the basis of the medium score (ranking), of the number of reviews, of the % of thrilled people and more with the chance to define time intervals and/or geographic areas and to segment according to sex.
Through the semantic analysis of the comment released by the customer/user, the positive/negative opinions are identified and bundled according to the topic (prices, staff, restrooms, car park, entertainment activities, menu, cleaning, etc.) according to the market sector they belong to (shopping centre, restaurant, clothes shop, etc.); the most frequent opinions (positive and negative) are reported; finally, it is possible to compare the results relative to a shop or a brand (ex. competitor) in order to recognize strengths and weaknesses.
All the reviews can be selected through customized filters and examined individually. If you are the owner of the structure to which the review is directed, it is possible to answer quickly connecting directly from the software.