As the value of hyper-personalisation is now universally accepted as offering the greatest returns in marketing, marketers are no longer asking whether they should hyper-personalise or not, it’s a given, but you do need to know how to accurately measure it..

According to Statista, 33% of marketers now spend more than half their online marketing budgets on personalisation. If you don’t, you are not maximising your budget efficiently.

Predictive personalising email software (PPS) has become the leading tactic used by marketers to improve their campaign performance. Information technology leader Accenture, reveals that 91% of consumers are more likely to shop with brands that provide relevant offers and recommendations.

But how can marketers measure the ROI of personalisation? How can you prove that your efforts are working and worth investing in?

This article is about the ROI of personalisation and what marketers can do to measure effort and fine-tune personalisation strategies, especially in the wake of privacy concerns. We’ll also cover zero-party data, the near-death of the third-party cookie, core metrics and how to better quantify the impact of your marketing campaigns.

Measuring the impact of hyper-personalisation

Hyper-personalisation can open up new ways to boost revenue and conversions. It can also help you acquire and retain customers and stretch your marketing spend further. But evaluating the ROI of personalisation isn’t easy, especially with siloed data and tools.

Siloes stand in the way of a fluid customer experience. Fragmented tools hinder cross-communication and leave marketers with an incomplete picture of their customers, resulting in broken customer experiences and irrelevant messaging. Removing these silos and the friction between systems enables you to finally see the compound effect of hyper-personalisation on your bottom line.

The compound effect of personalisation on revenue

Conversion Rate and Average Order Value (AOV) are two key metrics that directly impact revenue, and which can be easily increased through personalisation. In the above example, which is based on a mid-size ecommerce business, row one represents the company’s baseline, pre-personalisation. In the second row, we see that boosting the conversion rate by 10% through personalisation results in a 10% uplift in both revenue and Return on Ad Spend (ROAS).

If the business then also boosted its Average Order Value (AOV) by 15%, again through personalisation, the compound effect of these changes results in a 26.5% uplift in both revenue and ROAS. Although Return on Ad Spend (ROAS) is not directly impacted by the changes in the conversion rate and AOV, by improving the funnel a business will automatically make its ad spend more efficient.

By this we don’t mean identifying the right audience segments, segmentation is not personalisation. We mean serving each consumer with hyper-personalised product selection pertinent to their criteria for selection and purchase. Anything less than PPS software can’t do this.

You can avoid marketing waste, and no longer throw money away by serving up product offering to consumers with little to no chance of converting. No wonder many retailers have become used to enormous rates of returns (RoR). This will, of course, also have a positive impact on customer acquisition costs (CAC).

It’s important to note that these figures can vary from vertical to vertical, but it is clear to see that implementing a personalisation program has a huge impact on the key metrics and KPIs.

leading global research company McKinsey offers that personalisation can deliver 20x times the ROI on marketing spend or more. While marketers have been employing different methods of personalisation for the last two decades, meaningful personalisation – which involves identifying the unique traits of each customer, wasn’t possible until recently. The stark reality is that the tools simply didn’t exist to deliver truly relevant content and offers to customers on an individual basis.

Average order value and conversion rate directly impact revenue. Using predictive personalisation software, you can boost your impact in these two areas. However, marketers can track other metrics to maximize the ROI of their hyper-personalisation efforts.

Key metrics to track to gauge your personalisation efforts 

• Incremental Conversions: net conversions that come from personalisation which are over and above the control group’s conversion value. They are expressed in numerical terms over the benchmark number.
  
• Incremental Revenue: the net revenue generated from personalisation over the control group, usually expressed in monetary terms, cumulative or absolute, over the benchmark value.
  
• Conversion Rate Uplift: This is the change (increase or decrease) in the personalised version’s conversion rate over the control group, and it is usually displayed as a percentage. By tracking conversion rate uplift, marketers know how effectively their personalisation strategy contributes to revenue.
  
• Average Order Value Uplift: This metric provides the net increase in the average order value of a test group against the control group. It is expressed either as a percentage or in monetary value. In ecommerce, it quantifies the personalisation-led extra order values from the same customers.
  
• Significance: A campaign or hyper-personalisation is said to have high significance (or statistical significance) if a particular personalisation has shown visible effectiveness over its control group. This effectiveness usually measures a positive change in impressions or increased uplifts like conversions or average order value.
  
• Email ROI: Despite the recent changes, email remains one of the most popular communication channels. Along with engagement metrics like open rates, conversion rates, CTR, and ROI-focused metrics, such as click-through-revenue help to attribute revenue generated by email hyper-personalisation.
  
• Sales /revenue from clicks: This metric provides your personalisation campaigns’ total sales or revenue figures and represents gross sales or revenue figures. Usually, these metrics track sales or revenues that are the outcome of specific personalisation efforts.
  
• Web push ROI: This is one of the best-performing channels for engaging your opt-in subscribers. Successful web push strategies revolve around one-to-one individualised messaging based on a customer’s needs and historical or predictive behaviour. Combined tracking of opt-in and engagement metrics helps measure the ROI of web push personalisation.
  
• Mobile app ROI metrics: Mobile apps are an essential part of an omnichannel marketing strategy. While you spend time and money building your app and getting downloads, it’s essential to understand and measure your mobile app’s performance to determine ROI.
  
  One of the core metrics is new user acquisition and recurring engagement on the app. By tracking the acquisition, engagement, and retention metrics, you can determine the success and ROI of your mobile app campaigns.

Marketers may also want to track micro-conversion goals, such as page views, add-to-cart ratio, sales ratio, and other custom-defined metrics.

To succeed you must integrate and unify your marketing channels, by adopting PPS software sooner rather than later you can deliver relevant and personalised offers and communications immediately.

SwiftERM offers hyper-personalisation software as a 30-day free trial, to establish viability. 

SwiftERM is a Microsoft partner company..