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Measure up against competition and define steps for brand enhancement
Apiron Technologies’ client is one of the most successful independent German distributors of a wide range of components, peripheral and software products in Germany and all over Europe with a strong growing presence in the Scandinavian countries.
The client’s product is a leading innovative solution, already sold to more than 50 million happy customers worldwide. Apiron Technologies was assigned to perform a competitor and marketing analysis for the specific product in the Scandinavian markets and Italy.
The methodology approach includes data crawling, natural language processing (NLP), data analysis, and finally reporting of the results. Although the crawled reviews are in non-English languages, namely Danish, Finnish, Norwegian, Swedish, and Italian, all the information has been translated using in-house technology tools.
During the Natural Language Processing (NLP), two methodologies were applied:
• Sentiment Analysis Algorithms
Processed reviews and marked them as positive or negative.
• Meaning Extraction Techniques
The main topic and subtopics of each and every customer review were segregated. Based on these results, the most important product technical specifications (features), product price range and brand awareness were identified per product category and specific client base.
In summary, the following data analysis methodology was applied:
Data mining/Data crawling
Searched the web and gathered data related to customer reviews and product specifications via Apiron Technologies' in-house proprietary software.
Natural Language Processing (NLP)
Processed and analyzed reviews via machine learning-based meaning extraction tools in order to isolate the product specifications that are at the top of the customers’ interests.
Isolated the top product specifications from the crawled data and based on the top selling products per data source, the respective client’s products were positioned accordingly.
All these tasks have been achieved via Apiron Technologies in-house data science and AI platform: Pythia.
Having gathered specifications and product price ranges as our main criteria, the company positioned its client’s products in the market against their competitors. For the analysis the company used exclusively data that are available online. Key metrics for the analysis output were:
• The quality and features of the competitive products based on the specifications that the customers were interested in.
• The price range for the respective products and brand awareness.
Our report, a result of data mining and expert analysis, was presented to the marketing department as the basis to plan the next steps for those markets. More specifically:
• Provided the most important features and specifications by price range, competitors and user insights per country.
• Identified the reasons product market penetration for Italy was so low based on demographics and market analysis.
Product review customer insights example
The following example of razor products depicts quality ratings of the brand and the competition. Results were generated by a sample of 39K reviews from a total of 542 SKUs for the UK market (Dec2020). The Research and Development department was able to use the analysis results to improve an existing product or launch a new product based on customers' reviews.