4 Methods AI Helps Rising E-Commerce Platforms Compete with Main Sport Distributors

Over the previous 12 years, pc and online game distribution methods have undergone a seismic shift. Gross sales of digital video games exceeded these of bodily copies for the primary time in 2013, and the development was additional accelerated by the 2020 lockdowns. In Italy, for instance, the primary week of confinement led digital recreation downloads to skyrocket by 174.9%.

Wanting forward, the market is poised to proceed rising, with Statista projecting it is going to develop at a CAGR of 5.76% between now and 2027, ultimately reaching a market quantity of $25.4 billion by the tip of that yr. 

Regardless of this, competitors stays fierce. The digital video games market is dominated by solely a handful of platforms, and with 94% of spending happening digitally, that leaves little or no room for brand spanking new entrants. Established gamers — similar to Steam and Epic Video games Retailer within the PC sphere — benefit from this to impose hefty charges on publishers. 

For these main entities, integrating AI into their operations is second-nature. Nonetheless, for smaller, rising platforms, AI might be a game-changer — one that enables them to problem the incumbent oligopoly. 

Whereas replicating profitable AI implementations requires cautious consideration of platform-specific traits and operational contexts, listed below are 4 methods wherein AI might help fledgling e-commerce corporations compete with digital distribution giants. 

#1: Enhancing fraud detection

On gaming platforms, fraud occurs at a a lot bigger scale — and extra recurrently — than in different e-commerce verticals. Given its capability to course of and analyze huge quantities of transaction information, AI’s algorithms can promptly determine suspicious patterns or anomalies. 

By scouring by in depth transaction databases, machine studying algorithms can adapt and acknowledge fraudulent operations, starting from unusual consumer behaviors to irregular fee schemes and purchases from atypical geographic areas. 

In conventional rule-based methods, a few of these indicators may go unnoticed, hindering an organization’s skill to detect fraud and exposing it to potential monetary losses. 

At our firm, by implementing AI-powered software program — developed by a 3rd celebration — we’ve got prevented roughly 95% of fraudulent transactions. We additionally work hand-in-hand with know-how. As soon as an operation is flagged as doubtful, our supervisor personally critiques it. Digital recreation keys will not be launched to the client till the acquisition has been manually permitted by our supervisor. 

#2: Streamlining Buyer Assist Queries

In e-commerce, AI-powered chatbots are one of the crucial frequent functions of synthetic intelligence. 

Since there are a lot of options out there already, chatbots are comparatively straightforward to implement, even with out historic information. As a result of they’ll study from consumer interactions, chatbots yield outcomes virtually immediately, and assist corporations scale back their want for buyer help workers. 

Moreover, they liberate time for the present buyer help brokers. 

In our expertise, most queries acquired — round 70% — are fairly easy and repetitive. Examples embrace:

• Is the sport obtainable for buy?
• When can I obtain the sport key?
• How do I activate my license key? 
• What’s the standing of my order?

In 80% of those circumstances, our AI bots have been fairly profitable at serving to our customers without having to switch them to a reside operator. Thus, we are able to say that our bots cowl roughly 56% of our incoming help requests, liberating priceless assets that had been beforehand poured into help workers in order that we are able to use them elsewhere within the firm to boost our development. 

#3: Figuring out UX conversion-driving patterns

A standard dilemma e-commerce-oriented enterprise house owners face is figuring out these components that efficiently drive conversion and those who don’t. 

That is one other space the place AI might help, by gathering consumer information that pinpoints recurring behavioral patterns that both lead or deter conversions. Primarily based on this information, corporations could make UX-centered changes to their web site. 

Moreover, AI can create buyer segments that increase the effectiveness of selling efforts. Since it could actually create consumer profiles throughout numerous dimensions, AI can uncover connections and group look-alike segments that may not be apparent by guide critiques. For instance, prospects who buy GTA 5 may additionally be excited about video games from a distinct style that, in precept, bears no relation to GTA 5. 

To facilitate this, we’ve got applied a third-party AI personalization resolution from Retail Rocket. By leveraging historic buyer buy information, this instrument helps us accomplish a number of duties, similar to offering customized product suggestions — each on our web site and thru electronic mail — and figuring out relationships between merchandise, enabling us to counsel complementary purchases. 

Moreover, we are able to additionally time our prospects’ subsequent potential buy. This additionally improves our timing for advertising and marketing messages. All in all, we are able to proudly say that these efforts have bolstered our gross sales by way of advertising and marketing channels by roughly 15%. 

#4: Forecasting gross sales

Given the time-sensitive nature of the gaming trade — for example, Steam imposes constraints on what number of keys publishers can generate — efficient forecasting is essential. 

Right here, we’ve got applied an easy AI mannequin that’s based mostly on two main strategies: time collection forecasting and regression evaluation. 

By detecting patterns, the previous helps us predict future gross sales figures and adapt to seasonality, which is a crucial issue within the gaming subject. Alternatively, the latter assists our workforce in establishing relationships between gross sales information and different variables — demographics, pricing, product classes, and extra. 

Since there are large divergences in these parameters — for instance, there are sports activities video games launched yearly, similar to these by EA Sports activities, and different technique video games that span throughout many years — getting these crucial components proper is of paramount significance for correct forecasting. 

We first began with this within the spring of 2024, so, as of now, our outcomes are just like what we had been reaching with out AI. Nonetheless, we anticipate that as we additional calibrate and refine our mannequin, and accumulate extra historic information, our accuracy will considerably enhance over time. 

Remaining ideas

In some fields, similar to gaming, AI can develop into a democratizing issue — one that allows rising, high-potential platforms to compete with established behemoths. 

Having stated this, to completely understand its potential, it isn’t a lot about merely integrating AI for the sake of it, however about doing it proper. 

For smaller corporations that can’t afford to keep up an in-house workforce of AI specialists, a viable resolution is to make the most of present third-party software program. A few of these ready-made options can be utilized by common builders, even when they don’t seem to be specialised in AI. 

My suggestion is that you don’t transition all your workload immediately to AI. As an alternative, take a gradual strategy. For instance, ask AI to deal with 10% of consumer queries, or to dynamically worth 10% of your merchandise. 

Final however not least, keep the human contact. Having folks assessment the standard of AI’s help may be very helpful. As AI proves its price, you possibly can develop its scope inside your group.