By Russell Loarridge, Director UK, ReachFive

Marketers these days are up against it. They have many diverse marketing channels to communicate across; the competition is stiffer than ever before; the buyer journey is increasingly fragmented. It isn’t as easy or straightforward as it used to be, so brands, retailers in particular, need to work hard at differentiating themselves from their competitors. One way to achieve this is to develop strong and relevant content. But, more importantly, it is essential that marketing delivers these messages in an ultra-targeted fashion. This means personalisation. Although, often data that is necessary to drive these sorts of campaigns is stuck across silos, which doesn’t make it easy to build a true view of a customer.

Many marketers would agree that this situation makes personalisation difficult. 83% of marketers understand and accept that their customer data is scattered across various departments within their organisation, appreciating that it is disparate and disconnected*. Consequently, for many, the problem gets worse – this data is often compartmentalised, unusable and becomes outdated quickly. This means that brands must develop stronger and more robust data management strategies and processes, so that successful personalisation can be achieved for the business.

In light of the increased trend towards personalisation, this might just sound like standard, expected best practice for some. But it’s more than that. Consumers crave targeted marketing. With 72% of consumers admitting that they are set to change brands after just one bad experience, it stands to reason why it’s so important to deliver personalised marketing accurately and effectively to customers. Russell Loarridge, Director UK, ReachFive explains how brands can drive personalisation more successfully – while holding onto customer loyalty at the same time – by making better use of customer data platforms (CDP) and CIAM (Customer Identity and Access Management) solutions.

What is the vision for data across all marketing channels?

Developing a clear and shared vision of customer data across all marketing channels is a prerequisite for marketing innovation. But, reconciling this customer user data and activating it across the several marketing channels available today is a big challenge. This is especially problematic when you appreciate that data needs to be gathered and interpreted from around 28 different data sources in order to create effective customer engagement**.

Now, add in the fact that the majority of consumers buy products for people other than themselves (e.g. children, partners, parents, and friends) at some point, if not regularly, will approach different product purchases with different motivations. Therefore, they might abandon carts for an array of reasons at different times. What does your siloed, inaccessible data tell you about these scenarios? Is the identity of the shopper the same as the recipient? Was this a luxury purchase that was abandoned at the last minute because it just wasn’t necessary, or because the shopper found it cheaper elsewhere? Did something in your checkout process put the potential buyer off? How is your website collecting, storing and using data effectively in these scenarios?

The challenge is complicated. The struggle is real. Brands are becoming increasingly equipped with Customer Data Platform (CDP) solutions to support capturing and organising data from multiple online and offline contact points so that they can exploit it intelligently. For this technology to succeed, it must enable marketers to centralise data, remove duplicates, and reconcile it, in order to strengthen knowledge about their customers for marketing. In the end, these platforms should create better personalised experiences, improve marketing campaign results, and evolve product offerings. But, this is only possible if there is a clear and shared vision for data management within the organisation – one that joins up data silos to make insights truly actionable.

Untangling the problem that is data chaos

The reality is that in aiming to set and execute this vision for data, many brands face what we call a ‘silos and chaos’ scenario. This is because most data processing within systems – e.g. CDP, Data Management Platforms (DMP), ETL (Extract, Transform & Load) tools – is based on probabilistic reconciliation. Blocked by poor data quality, data warehousing and integration, systems cannot reconcile brand data without a lot of preparation work upstream (e.g. data engineering). This process often requires heavy technological investments and only ensures an average reconciliation of 25% – 50% of the data.

Deterministic matching, in contrast, based on rich, verified and secure identity-based data does not only achieve 100% matching, that supports marketing more effectively, but it improves the quality of the data that feeds personalisation algorithms. The customer data collection, cleansing and unification capabilities supported by advanced CIAM (Customer Identity and Access Management) then allows companies to move to an optimal ‘silos and identity’ configuration for data management. This helps marketers better understand who they market to.

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CIAM is a true complement to CDP

If we come back to our example of who is really visiting a brand’s website – what if that brand had CIAM in place? They’d be able to successfully work out who is visiting their website, for whom and why they are shopping, and gather appropriate data to deliver personalised marketing effectively. During online shopping, a brand’s CDP typically centralises and stores transactional data from ecommerce and point-of-sale systems. But, it does not bring up data related to customer identity. Without this missing information, it can only deliver part of the value that data promises. Identity information – email, phone, social identity, loyalty ID – is the key variable for success here.

Furthermore, one of the vital challenges CDPs face is to be able to attach anonymous, cookie-based data to a known customer from the moment they create an account. CIAM, in contrast, collects zero- and first-party customer profile data, including communication preferences and consent.

Added to this is the fact that we live in a world where consumers often move from one device to another. From the time they jump from mobile phone to tablet, to computers, to connected TVs, it is important that the message they receive can follow them wherever they go. CIAM reconciles all available data points for marketers to an identity, including those collected in first- and second-party scenarios.

CIAM is a true complement to CDP. It makes it feasible to manage identity and treat it as a data source, in the same way that purchasing or browsing behaviour are sources. It links all the data and allows the CDP to achieve its full potential by ensuring that all transactions and interactions are correctly linked to a customer’s identity. Together, they deliver and drive personalisation.

It can be concluded that CDP and CIAM technologies complement each other. Together they enable brands to recognise their customers across all touchpoints, and gather and use appropriate data accordingly with their identity. This combined approach to data management ensures better marketing and recommendations. It encourages the development of relevant marketing offers and products – ultimately, it sets the prerequisites for personalisation, better customer relations and more customer loyalty.

Aside from this, a truly aligned and connected data-driven strategy is a key asset to the marketer’s organisation. This is because data helps organisations to support and manage online and offline customer relationship building. It also drives sales and broader operations like product category management – all for enhanced engagement, long-term loyalty, and profitability. After all, it is the bottom line that counts. In this case, it’s the effective use of data that can make that ultimate difference.

Published 24/11/21

*Source : Acquia CX Report 2020

** Source :–marketing-and-commerce/hux/how-to-win-on-customer-experience.html




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