How Businesses Can Achieve Personalization at Scale

How Businesses Can Achieve Personalization at Scale


Personalisation works. We know for a fact that it can help raise the ROI of marketing spend by between 5 and 8 times, and lift sales by at least 10%. That’s according to McKinsey figures. We also know that sales rise when customer web experiences are personalized, and personalized calls to action raise conversion rates by over 40%.

But personalizing the customer experience isn’t easy, and often requires investment in technology and processes. You need to have technology that can recognize your customer, a marketing team that understands how to approach them, and a communications strategy that can deliver the right message or content to that particular individual.

The wider your audience, the harder it is to achieve meaningful personalisation for each person in it.

Get your personalization approach wrong and there is always a danger of appearing creepy. When marketers first latched on to the value of remarketing, many customers were freaked out by a brand they’d recently interacted with supposedly following them around the web.

Although remarketing delivers strong results at getting people to return and complete their purchases, it’s important that your personalization appears human rather than aggressive and robotic.

Writing in Harvard Business Review, a team of McKinsey marketers advised that personalization approaches are tested on real customers to see what really works.

Data, decisions, and distribution

Mass personalization starts by gaining command over your data. The key here is not just to gather it, but to gather it in such a way that you can get a meaningful understanding of your customers from it.

Winning the data war often means upgrading and integrating existing systems to create more flexible systems that are capable of giving structure to vast amounts of data. Modern data systems need to incorporate data such as purchase history and marketing response data from a wide range of sources, including apps, POS, and website.

Some of the more sophisticated customer data platforms are able to assign propensity scores to each member of your audience. These scores measure the likelihood of your customer responding to your brand in some way, either by purchase or by consuming your content. The CDP will track the individual’s interactions with your brand and raise or lower their score accordingly, helping to adjust how you communicate with them.

Propensity scoring is a key way for many organisations to personalise in a meaningful way at scale.

How your brand decides to respond based on the data you have collected is a major part of winning at personalization. Even with the most sophisticated scoring system that’s currently available, your brand still needs to craft a personalization strategy that works for each customer and creates a meaningful interaction.

Your business needs to create a process that incorporates a perpetual learning cycle so that you are constantly improving your personalization approach based on learning from the results of your efforts.

This learning may happen automatically, through AI, as sophisticated CPD systems learn which responses to customer interactions will best generate conversions. Or it may happen through your team’s own analysis and predictions.

All this needs to be supported by an effective content management and distribution system. You need to decide what content, offers, and experiences you are delivering to each customer, and how you are going to reach them. Achieving a seamless personalization experience across all the customer touch points is tough; get it wrong and you may confuse the customer with missed messages.

Personalisation for B2B sales

Personalization is a key issue for sales teams in the B2B arena. Research suggests that leads that are approached with personalized content produce 20% more sales opportunities than those approached generically.

Many sales-driven organisations are leaning on social media for the personalisation information they require. Canny brands have started to identify the key intent signals that can indicate someone is ready to buy.

In the B2B arena, this can mean something like a job change, which indicates someone may be interested in asserting themselves in a new role by making B2B buying decisions. Sales reps may also keep an eye on who is posting what in social forums such as professional networking groups on LinkedIn, as this helps indicate who is thinking about what key business issues.

But sales agents aren’t just scouring social media trying to spot warm leads. There is also a range of social media information-scraping tools available to help sales teams spot leads using a range of filters that look at measures such as the size of a company an individual belongs to, their industry, and their job title. Glass.ai is one such AI research assistant, helping sales teams identify hot prospects using advanced filters that scour social channels and a range of other sources of information.

These technologies are providing new opportunities to personalise approaches to sales targets, particularly in B2B.

Customers in both B2B and B2C markets increasingly expect their brand experiences to be personalised. It’s a way to show your audience that you understand them and that you’re aligned with their needs.

Personalisation can help shape a customer’s journey and put fewer steps between them and the conversion process. It can help you get closer to your customer, increasing engagement and improving retention. Achieving personalisation at scale requires brands to not only get the technology right but also to really start to understand their customer.

Marketing systems may be ever more sophisticated, but the onus is still on marketing managers to gain insights into their audiences in order to personalise their approach effectively.

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