How to increase sales by selecting the right contacts thanks to Artificial Intelligence
The Call Center represents a very important means of contact for companies, as it allows the brand image to be conveyed while maintaining human contact and making it possible to customize the experience according to the customer’s needs. It is no coincidence that companies belonging to various sectors, from Utilities to Telcos, and even debt recovery and non-profits, use it to improve their results in terms of acquisitions, retention, cross-selling and collection, contributing to constant growth of this market, as we have already seen in this article.
Artificial Intelligence and predictive value models for effective debt collection
Debt collection is a very complex activity which, to be successfully completed, requires companies to have in-depth knowledge of both the profiles of the debtors and the debts to be recovered. We have already dealt with debtor analysis here, therefore today we will deal in more detail with the study of debts to be recovered with Artificial Intelligence, which represents a complementary and necessary activity in order to allow companies to implement the best strategies to achieve their objectives.
Utility and Anti-Churn: how to increase retention rate with Artificial Intelligence
In today’s liberalized and hyper-competitive energy market, one of the biggest challenges for utilities is to lower the churn rate. We have already discussed in this article how important it is to keep customers loyal to your brand, not only in terms of brand image, but also and above all in reference to company turnover. Today we will try to define how and why a utility today can succeed in retaining its consumers while increasing its revenues and without significantly affecting costs.
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.