How the Fake Web is Impacting Business Economics

By Guy Tytunovich, founder and CEO of CHEQ

Fake accounts and inflated metrics have become a recent hot topic in the world of finance. Many of us were surprised to learn that JP Morgan invested millions in a FinTech startup, only to find that the growth of new accounts may have been manipulated to include inauthentic users. These situations result in legal nightmares, business costs and issues of trust, and pose a question to businesses worldwide: How do you know if the organizations and customers you work with are genuine users and not bots or humans with malicious intent?

Today, it is widely considered to be the era of the ‘fake web’ – and all businesses are feeling the impact to some extent. Within the financial sector specifically, CHEQ data found that 13% of website visits come from bots and fake users. In many cases, institutions are even paying for these potentially harmful visitors to arrive on their websites through paid advertising or other marketing tactics.

With this in mind, many enterprise financial organizations are questioning how they can effectively vet mergers, acquisitions, and other critical business decisions. When you add on the already volatile nature of investing, and the current downturn in the macro economy, these tasks become even more difficult. Throughout this article, we will discuss common ways that the fake web impacts these decisions, to provide institutions with an initial list of what to look for when determining if an opportunity is worth pursuing and moving forward with.

Growth metrics

One of the many things investors use to determine whether an organization is worth investing in, acquiring, merging with or partnering with is the level at which the organization has been able to grow. This includes the analysis of metrics like customer acquisition cost (CAC). In cases where an organization has bots and fake users interacting with any assets along the customer journey – advertisements, content, email marketing campaigns, sponsored content – the cost to acquire a single customer can appear higher than it actually is.

For example, an organization may be currently spending $1000 to acquire a single customer through these channels. But if even 10% of that budget is wasted on bots and fake users, their true CAC would likely be closer to $900. In this example, a $100 loss may seem unimportant, but consider the impact this would have across an institution that invests in acquiring millions of customers. The result would be incredibly misleading acquisition costs that could inaccurately determine the business’s future.

Conversion rates

When considering whether or not to take financial action on another organization, institutions also consider the rate at which this organization is able to convert website visitors and those with initial interest into paying customers. This metric is commonly referred to as a conversion rate. If bots and fake users are present though, the organization might think their conversion rates are quite low at certain points in the funnel, and potentially unusually high at other points.

For example, if a bot is testing stolen credentials in a top-of-funnel form, the business will think that form is converting at a high rate. But if that bot is then unable to complete a purchase down the line, the business will think there is a drop-off at lower funnel conversion opportunities. Needless to say, bots and fake users paint an inaccurate picture of reality and can sabotage or mislead financial decisions.

Lead generation and pipeline

If a larger institution is looking to make an acquisition or merge with another company, they will want to see how much pipeline the other company is bringing in through paid and non-paid channels. Similar to the issue caused to conversion rates, pipeline and forecasting can become heavily influenced by bots and fake users. Imagine a new lead comes through the funnel, and the sales team is tasked with following up with that lead to ultimately determine the potential deal size and likelihood to close.

Now imagine that the lead is not a genuine user. If this happens even 10-20% of the time, valuable resources are wasted on trying to qualify invalid leads. During that time, attention can be diverted away from legitimate leads that can actually contribute to pipeline and forecasting numbers. Again, data will become skewed, and future outcomes become unpredictable.

Customers and accounts

Perhaps most closely related to the aforementioned JP Morgan situation is the issue of fake accounts inflating the number of users and active usage of apps or platforms. Organizations want to show that they are not only closing deals and increasing conversions and pipeline, but also that their customer base continues to grow and remain active within their platform. However, as the average developer can tell you, it is not difficult to inflate account numbers through the creation of bots and fake users. This can be done internally by corrupt or malicious business owners, but it can also be done without the business’s knowledge by bad actors online. This is misleading to any business looking to acquire such a platform or app and can lead to inaccurate forecasting, abandoned deals, and even legal fees down the road.

Conclusion

In general, nearly every metric that businesses are evaluated on for mergers, acquisitions and major financial decisions can become skewed by bots and fake users. For this reason, it is important for both parties involved in these decisions to complete due diligence and do their best to ensure there will be no unwelcome surprises in the future. Especially today, when the creation and deployment of bots is becoming more democratized than ever.

The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.