With the rise of big data, e-merchants can benefit from various indicators to analyse their customer’s browsing behaviour. However, transaction data are still too often overlooked. A combined analysis of data from the order (customer’s name and email address, type of purchase, cart amount, IP address) to the authorisation request (type of bank card, name of the issuing institution) provides a wealth of information and opens up many possibilities for optimisation.
Identifying transaction failure factors
Analysing transactions from payment to final status (payment accepted or refused, refund requested) helps e-merchants understand the reasons for their success or failure. It also helps them to take action and adapt the user experience to different scenarios according to multiple criteria: display order of payment methods, personalised payment pages, risk profile, dynamic 3D Secure, etc.
In order to detect and address threats as soon as possible, standard customer profiles must be defined in order to focus attention on all other behaviors. Knowing your customers is key to ensure optimal security.
Implementing custom fraud protection is the future of merchant websites
Identifying transaction data will enable e-merchants to accurately fight against fraud, without negative impacts on customer experience, while maintaining their conversion rate.
Information such as the acquisition channel used by customers, their purchasing behavior or the card country of origin can help them spot profiles deemed reliable or not. E-merchants can then decide to strengthen or lower the security rules triggered upon payment.
Knowing the actual performance of your marketing actions
Aside from transactional considerations, which fall within the scope of the Finance Department, payment data analytics is also a powerful tool to measure the efficiency of marketing acquisition campaigns. In the case of performance-based campaigns, for instance, merchants can clearly identify visitors who clicked and bought, as well as subtract those whose payment failed or who asked for a refund or a chargeback. This indicator is called the net conversion rate which serves both financial and marketing purposes.
Overall benefit of exploiting payment data
Selling online requires new client acquisitions. E-merchants invest significantly in lead acquisition campaigns, SEO and CRM to attract and convert more customers. Yet, all too often, payment tunnel optimisation is not addressed. That’s why HiPay has developed value-added tools and proprietary technologies around “payment intelligence” to be able to consolidate all payment data for a specific merchant and analyse it with algorithms created by teams of data scientists.
Information drawn from such analyses aims to optimise the three main performance indicators: the conversion rate, the fraud rate and the success rate. In other words, this means more sales without risk.
About Grégoire Bourdin
Following his experience in audit at KPMG, Grégoire Bourdin, 37, served as Chief Financial Officer at HiMedia from 2008 to 2011 where he restructured financial operations, supervised all French and foreign subsidiaries, and accompanied the integration of acquired companies.
In 2012, he joined Benjamin Jayet with whom he led a dynamic investment strategy and coordinated numerous operations. Expert in the digitization of the banking sector and passionate about new models developed by Fintech, Grégoire Bourdin founded Treezor in 2014, under the aegis of BJ Invest.
HiPay is an expert in payment services offering online publishers and retailers next generation solutions to maximize their revenue while limiting their risk. HiPay brings added value to transaction processing with industryleading solutions in international payments, risk management and business intelligence.
This article is part of the exclusive Online Payments and Ecommerce Market Guide 2016, an educational overview of the global payments industry. For more insights into the latest trends in ecommerce and e-payment methods developments please download a free copy here.
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