Artificial Intelligence and Phone Collection: assigning the best agents to the most complex practices
Debt collection campaigns can be very complicated to manage and the companies that manage them must take into account numerous variables in order to achieve their objectives, such as the propensity of a debtor to repay their debt and the economic value that has to be recovered. Currently, the processing method used by most companies dealing with Debt Collection consists of randomly assigning the contacts present in the lists to the operators, without performing any prior analysis on them.
Win-Back: recover your customers with Artificial Intelligence
We have seen in some previous articles how investing in retention is a fundamental factor for a company, allowing it not only to strengthen its position in the market, but also to increase its revenues. Despite efforts to avoid churn, it can still happen that customers decide to leave a company because they are dissatisfied or because they are intrigued by a competitor’s offer. In this case, companies need to invest in ad hoc strategies that are able to repurchase the lost customer, thus launching win-back campaigns.
Click-to-Call and Call-Me-Back, how to maximize inbound sales thanks to Artificial Intelligence
Acquiring a warm contact from lead generation campaigns (whether they are DEM, digital advertising or online comparators) has a high cost and can be complicated to manage, as we have seen in this article, but once obtained, companies have a great opportunity to succeed at closing sales.
How to predict the expected value of a recovered debt thanks to Artificial Intelligence
Companies that deal with debt collection can have different types of objectives, some related to the quantity of recoveries, others related to the quality, that is the value of the recovered amount. The first, as we have seen in this article, refers to how many positions you are able to recover in a given period of time, while the second, which we will cover today, refers to the overall value recovered from the debts treated.
How the role of the Credit Manager will improve in the future thanks to Artificial Intelligence
In this article we will focus on a figure who has recently been assuming an increasingly central position within companies: the Credit Manager. Due to the slow post-pandemic recovery, due to various factors including the outbreak of the war in Ukraine, risk management, and consequently the role of the Credit Manager, becomes vitally strategic in order to be able to maintain one’s business at competitive levels.
Artificial Intelligence for Anti-Churn: BigProfiles presents the new feature of its Platform
As we have already seen in one of our previous articles, the relationship between company and consumer develops well beyond the buying and selling phase and finds its maximum expression immediately after the customer becomes part of our customer base brand. It becomes essential for companies to be able to implement strategies capable of reducing the churn rate which, if uncontrolled, can have serious repercussions both on revenues and on the corporate image.
Phone Collection: how to identify spontaneous debtors thanks to Artificial Intelligence
Within many Phone Collection campaigns, there are important segments of debtors present that can be defined with the word “spontaneous”, that is: those profiles that will repay the debt without the need to contact and push them to do so. Among these we can find those who have simply forgotten that they had an overdue bill or who are waiting for a late salary in order to settle the monthly payment.
Banks and insurance companies in the digital age: how Artificial Intelligence shapes the future of these sectors.
Digitization is an unstoppable process to which companies in each sector have to respond adequately in order to maintain or acquire a strong position within their market. Banks and insurance companies are no exception, which in recent years, have seen a radical change in their own business models, following a significant reduction in the number of physical branches and consequent notable increase in the number of practices managed exclusively online.
Inbound and Artificial Intelligence: how to increase the conversion rate of Customer Service to Sales campaigns
Customer Service has a role of primary importance for modern companies: in addition to being a very important point of contact between company and customer, it also brings with it the possibility of being used to increase sales. In this case we are talking about Customer Service to Sales campaigns, within which we find Upselling and Cross-Selling strategies that allow the company to increase its revenues by offering its customers an upgrade of the current offer or the purchase of complementary products and services.
Artificial Intelligence applied to churn prevention: the future of customer relations
Customer loyalty is a fundamental objective for any company that wants to remain at the top of its market, whichever it may be, but to succeed it is absolutely necessary to invest time and resources both into identifying the problems that can lead customers to change company , in order to solve them in the shortest possible time, and also into the study of new strategies that are able to maximize retention.
How to achieve your goals with ease in B2B and B2C operations by making the most of Artificial Intelligence
In the current context in which innovation and digitization have become essential elements to ensure business continuity, every company, whether targeting B2B or B2C markets, needs to implement services capable of optimising their internal resources and, above all, to provide the best experience to their target market, whether it is other companies or consumers.
How Artificial Intelligence allows for the optimization of debt collection services of banking and insurance companies
The current economic and commercial instability is playing an increasingly important role in the world of debt collection, with particular reference to companies in the banking and insurance sector.During the pandemic crisis, both of these sectors provided the necessary liquidity to companies to relaunch themselves, but now, with the challenges arising from the increasingly uncertain geopolitical and economic situation, they must be prepared to face the growing difficulties that are arising as a result of the struggles of individuals and companies to pay their debts.