By Kyle Morris, CISA, Senior Manager in Compliance Success at Scytale AI, finalists in the Best Security Innovation In A SaaS Product (B2B, Small Business / SMB) category and Best SaaS Newcomer category in The SaaS Awards 2023

Personalization and data are fundamentally equivalent. You can only achieve personalization by gathering data. However, obtaining and using said data may prove something of a ‘Pandora’s Box.’

But what other options do B2B SaaS companies have when caught between this rock and hard place? Modern customers not only gravitate toward personalized user experiences, they demand it. But, at the same time, businesses are becoming increasingly concerned about their data privacy and the risk of that data being compromised.

So, what’s the solution? How can companies discover the advantages of hyper-personalization while balancing ethical and compliant data privacy regulations? We’re looking at hyper-personalization vs. data privacy and how to balance delivering personalized services while safeguarding user data and privacy rights.

Personalization vs. Hyper-personalization

To kick things off, I’d like to touch on what hyper-personalization is and how it differs from traditional personalization.

Traditional personalization, doesn’t go as far as most users (and most companies) would like it to. And so we look to hyper-personalization.

Hyper-personalization goes beyond traditional personalization strategies, (which generally do not consider individual users and their preferences.) Instead, it focuses on a granular, personal level. It does this by leveraging real-time behavioral data and advanced analytics and algorithms considering a vast amount of individual data.

One of the core differences between personalization and hyper-personalization is that traditional personalization uses historical data to create a tailored experience for a segmented customer group. Hyper-personalization, on the other hand, uses real-time data to provide contextually relevant experiences. Without getting into the nitty-gritty details of hyper-personalization strategies, it is often implemented through a combination of predictive analytics, AI, location-based tech, and machine learning.

“Let’s talk about the good, the bad, and the balance”…

Before I get to the tricky side of balancing hyper-personalization and data privacy management, it’s important to consider hyper-personalization’s business use case. A recent report from Mckinsey & Company shows companies that excel at personalization generate up to 40% more revenue than companies that do not invest in similar strategies. Additional evidence that confirms this is in the 2022 Gartner Customer Service and Support Survey, which reveals that up to 71% of B2C customers and 86% of B2B customers expect personalization during an interaction with a brand.

Companies that lean into this have seen benefits which include improved customer satisfaction and loyalty, a significant increase in ROI and overall reduced marketing expenses. In the B2B SaaS landscape specifically, leveraging hyper-personalization strategies has been seen to reduce customer churn, increase up-sell likelihood, increase customer lifetime value and dramatically reduce the load on customer support.

But this assumes that they’re doing it right.

A good example of a SaaS company in the B2B landscape that is effectively utilizing hyper-personalization is Hubspot. HubSpot’s tailored email sequences leverage hyper-personalization techniques to send tailored email sequences to individual leads based on a variety of behavioral data as interactions with previous emails and website visits. By leveraging these basic hyper-personalization techniques, they can increase engagement and conversions.

The bad: An inherent tension between hyper-personalization and data privacy

It’s only natural that customers and companies alike may want to shift down gears when implementing hyper-personalization strategies. After all, with a staggering rise of ransomware and an increasingly strict regulatory data privacy legislation landscape, it comes as no surprise that there are growing concerns around processing and analyzing personal information and the risk associated with security and data privacy compliance.

It’s no secret that hyper-personalization relies on obtaining and analyzing personal data. If done incorrectly or not in accordance with relevant security standards or regulations, your company may violate data privacy laws. This risk drives significant tension within the SaaS landscape as users become increasingly concerned about data privacy and how their data is being used – and they’re not the only ones. Governments continuously intervene and limit data collection and how it’s obtained and stored, and businesses are forced into playing compliance catch-up – and fast.

The balance: how to effectively walk the tightrope

SaaS companies can effectively balance hyper-personalization and imposing restrictions on data, but it will require a dedicated and intentional approach, and one that requires a ceaselessness regarding consistent security compliance. Here’s how:

Regulatory diligence

The onus is on companies to navigate the regulatory landscape. Businesses must comply with laws and regulations that apply to them regarding security and data privacy. A good example is The General Data Protection Regulation (GDPR), considered the most essential (and tightest) standard governing data collection. Among a plethora of security controls and requirements, GDPR requires businesses to allow all users the right to view their data, the ability to take that data and use it elsewhere, and the right to request that companies delete all data from their records. Depending on the type of data a business collects, location, and various niche industry-specific contributing factors, different regulatory standards or voluntary frameworks may apply or be best suited for your specific business.

Effective data governance

At the heart of data privacy management is effective data governance. For successful and risk-free hyper-personalization, companies must be able to manage and track their data usage, data location, and customer consent, both to meet regulatory obligations and improve user trust. To do so, companies must be strategic in how they use data and whether all data gathered provides relevant user experiences. This is best achieved by pinpointing and analyzing each data point to ensure that it serves a tangible purpose and adds value to the business and the user. One proactive way to achieve this is by conducting a data audit to limit data collection to what’s actually needed. A thorough data audit will give companies an exhaustive review of all the points and processes where they may come into contact with personal data. It will also assess and identify any areas of exposure regarding regulatory requirements, creating a fundamental baseline that businesses can continuously refer back to confirm whether or not they are meeting compliance requirements and customer expectations. In order to maintain consistent compliance and to ensure that they’re proactively mitigating risks and securing data, it’s best recommended to implement bulletproof security standards that meet the necessary requirements of a relevant compliance framework like SOC 2 or ISO 27001.

Anonymize data

In an attempt to bulletproof security gaps or risk exposure, many SaaS companies have found that anonymizing data helps create the balance between hyper-personalization and data privacy. By implementing techniques such as masking or tokenization, companies can remove any individually identifiable information while simultaneously using this data for analytics purposes. Data anonymization is critical for protecting confidential data from being exploited so that it can be used responsibly.

Conclusion

Ultimately, SaaS companies are finding themselves in a catch-22, and the only way out is to embrace a future of consent-based data collection. We’re not entering a new era; we’re already living it, and ignorance surrounding data privacy processes no longer suffice; for both users and companies.

Yes, users want hyper-personalized experiences and simultaneously demand greater transparency, autonomy, and security regarding data. But at the end of the day, you’re not on opposing teams.

By leaning into what users want and aligning with regulatory data laws, you’re protecting your clients and future-proofing your business, and protecting your own brand, reputation, compliance, and finances in one fell swoop while proactively increasing sales and bolstering business. Sounds like a win to me.