The website and mobile applications are the biggest revenue generating fronts for your online business model. And, you know they have to be protected. There are several Web Application Firewalls in the market, that can protect your website from DDoS attacks and XSS vulnerabilities. However, the online businesses of today face challenges from many other quarters. For example, you may not even know that the content you publish on your website is being stolen and posted elsewhere, impacting your SEO. You may be unaware that your competitors are scraping your pricing and product catalog information.
Bots are of two types, good and bad. You don’t want to stop the good bots, for obvious reasons. Good bots like search engine bots, social network bots and aggregator bots bring the much-needed visibility to your website. And, bad bots sent by third-party scrapers and your competitors, steal your content, scrape your prices, increase page load times, create unwanted pageviews, skew analytics, spam your web forms (comment / forums / lead capture forms) and create a bad user experience.
So, how do you check the invasion of bad bot traffic on your website or mobile application? For that, it is essential to know, how to identify the bot traffic coming to your website. This can be accomplished with either of the two methods:
In-house bot prevention teams are set up over time. They are constantly on the lookout for anomalous behavior on the website, which is investigated and traced to the type of bot activity. However, there are a number of limitations to an in-house bot prevention system, as the bots become sophisticated day-by-day and break the in-house defenses put in place.
The following table shows how in-house bot prevention teams hold up against anti-bot activities:
| Anti-bot activities | In-house bot prevention team | ShieldSquare bot prevention |
|---|---|---|
| Effort | Manual | Automated |
| Effectiveness | False positives/negatives | Zero false-positives |
| Response time | Delayed | Real-time |
| Bot detection accuracy | Hit or miss | Accurate |
| Bot classification | Laborious | Instantaneous |
| Bot activity audit | Manual dashboards | Real-time dashboard |
| Bot prevention | Manual, IP blacklists | Real-time, based on finger-print & incremental bot signature database |
| Ease of use/learning curve | Need to factor in team attrition and training time | Intuitive to use |
| Detecting advanced/sophisticated bots | Laborious, difficult and easy to miss. Playing catch-up with advanced scraper bots | State-of-the-art algorithms to detect changing bot behavior |
| Data science expertise | Not applicable | Machine-learning + human intelligence for varying bot behavior |
| Cost | Low startup costs, but will become unpredictable over time | Predictable, recurring costs based on monthly pageviews |
| ROI | Fuzzy | Easy to measure and realize the benefits from day one |
Relying on experts to handle the bot issues is the best way to curb the bot problem. Dedicated bot prevention solution will ensure that you are 24/7 protected against bots without having to build and maintain an exclusive In-house bot prevention team which typically would cost you more and be less efficient in combating against bots.
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