Product Profiler

The Product Profiler analyses your e-shop’s products and categorizes them into a set of predefined groups in order to inform about the composition and behaviour of visitors and customers with regards to products preferences. This facility provides the e-merchant with valuable information about the product of the own e-shop as the conversion rate of the product in relation to its visits within a certain time space. The results of the analysis are visualised for the users, thus the users can easy detect their best sellers as well as their shelf warmers.

The Product Profiler is based on the web tracking data that have been previously collected by the Data Collector and Consolidator module. These data is mainly based on the Piwik digital footprint of the eshop. The digital footprint connection is carried out by means Tracking code, previously included in the registrarion form.

A registered E-COMPASS cockpit user can navigate through this facility by clicking on the “Product Profiler” link on the top navigation bar.

Overview

A time period, from start date to end date, can be selected for the inspection of computed data about products. The dropdown list allows for different analysis and visualisations. In concrete, these analysis are:

• Product SWOT Analysis (by default)
• Trending Characteristics
• Product Typologies
• Product Typologies%

Product SWOT Analysis

Product SWOT Analysis gives an overview of the shop’s products and visualises how the products fare in regards to purchases (conversion rate) and visitors looking at these products. The derived information can help optimising sales. If a product is visited rarely but the conversion rate is high, for example, placing it in a more prominent spot on the web-site could improve sales. A product that has low visitors and low conversion rate, for example, should be checked in terms of pricing or maybe even replaced or removed completely.

The SWOT plot that appears in this option (see figure above) shows relationship between product conversions and visitors. Horizontal axis of the chart provides an indication of the amount of visitors for a product within the e-shop. Vertical axis shows the conversion rate of a product. Size of the points represents the total revenue generated by a particular product. In fact, if you place the mouse on an interest point, a label with the name of the specific product will appear as shown in the figure (for example: "Wella SP Luxe Oil Keratin Protect Shampoo 1000 ml"). Strategies for individual products can be assessed regarding which of the 4 quadrants in the chart they appear.

• Left-bottom: Low visitors, low conversions. This product shows little interest from visitors, as well as few sales.
• Left-top: Low visitors, high conversions. This seems to be a profitable product, having little web traffic oriented to it. With a proper promotion, this product could be more visited and create even more sales.
• Right-bottom: High visitors, low conversions. The product might be interesting but somehow visitors are not totally convinced to buy it. Checking product characteristics, features, price… could be a good option.
• Right-top: High visitors, high conversions. Attractive and profitable product, this product could be successful by itself, and following its promotion strategy seems to be desirable.

Trending Characteristics

The second option "Trending Characteristics" consists of a cloud of key words, in terms of products, that are computed from main preferences registered from visitor's activity.

The main aim is to assess if worth it boosting this products with a special marketing campaign or another type of advertisement strategy. In this regard, tools like text clouds are very useful to rapidly view the trending product characteristics, as shown in the figure above.

Product Typologies

This facility offers a different point of view for product analysis, by means of which, it is possible to check their typologies over time. These typologies are classified in different categories of products, mainly: Speciality, Convenience, and Unsought, as shows the following figure.

• Speciality: Specialized product (for example, "Last generation of Wella shampoo with kerain 1000ml")
• Convenience: Usual purchase product involving little reflection when buying (printer ink)
• Unsought: Product that customer was not looking for in the web

Product Typologies%

This option extends the "Product Typologies" facility by computing categories of products in percentage over time.

This graph allows three different visualizations: Stacked, Stream and Expanded, which can be selected by clicking on labels at top-left to show three different perspective of calculated data. In the example figure, the Stream option is activated. Specific values can be extracted by locating the mouse on plot.