BIMA Hangout – Single customer view – the missing piece of the puzzle?

By BIMA
25 Jun 2020

In a time where many brands will probably be reviewing their technology roadmap – and many may be going through a digital transformation driven perhaps by a customer experience vision, we at the data council thought it would be great time to delve into the unknowns of Customer Data Platforms (CDP’s), attempting to demystify these and deliberate whether achieving a single customer view is truly the missing piece of the puzzle.

In this first session from the newly reformed data council at BIMA, an expert panel discussed this at length and here are the key takeaways.

Joining our host and chair of the BIMA data council Paul Moss, Head Of Data Strategy at VCCP were:

Omer Artun, Chief Science Officer at Acquia

Eric Fullerton, Lead Product Evangelist at Acquia

Will Lowe, Chief Data Officer at Engine

Lisa Cousins, Business Strategy Director at Huge Inc

Download the webinar here.

Key data & customer data challenges:

The data landscape is very complex and quite confusing, there are so many vendors, diagrams and acronyms, it can be difficult to navigate.

Further to this as relationships with customers become ever more digitally focussed, it’s also becoming increasingly more difficult to have intimate relationships. There are more channels, touchpoints & customer data than we’ve ever had before. As a result, we can lose sight of the customers’ intent & the ability to have personalised relationships with them.

When we break it down though, there are 3 key things most brands are trying to achieve with their customer data:

  1. Building intimate relationships with customers digitally – match offers, content  & messaging to individual users.
  2. Drive efficiency in marketing spend / incremental returns on every media dollar spent
  3. Find the right balance of privacy & personalization.

One thing that is absolutely crucial when trying to achieve effective utilisation of customer data, is that we shouldn’t try to do too much at once.

Firstly identify what is your longer term vision & strategy – what is the key challenge to be solved – then be use case driven, breaking down the overall strategy into smaller more manageable chunks. When you take this approach it will enable brands to move away from simply activating yet another campaign, to being data first, using customer insight to do fewer campaigns & messages – but doing so much more effectively.

What specific challenges can a CDP help to solve?

The main purpose of a CDP is to achieve customer centricity, it allows you to understand your customers better, their preferences, their needs and their value.

The CDP helps to stitch all the touchpoints, channels, actions & conversations from each customer together to achieve a single customer view. When used correctly you can utilise the insight gathered to segment your users into cohorts that can be activated with messaging that’s completely tailored to their needs. Ultimately building much more intimate digital relationships with your customers.

The 4 main challenges that a CDP can help to overcome are:

Centralisation of Data – Collating, storing and managing all customer data into a single platform (purchase history, marketing touchpoints, website behaviours, support history etc)
Identity stitching – The ability to collate a complex matrix of individual customer data points together to create a single customer view
Customer Analysis – Improvements in speed and effectiveness when looking to analyse customer data at scale and build cohorts of customers to deliver better, more relevant customer relationships across channels, even predict what needs they may have in the future.
Orchestration engine – The ability to activate audiences rapidly across platforms including sequencing messages across platforms to deliver the right message to the right customers at the right time.

How do CDP’s differ from CRM Systems?

A CDP is a platform that supports any combination of all of the above but this does not mean it replaces your CRM system, rather it exists alongside. CRM databases are operational systems for collecting customer data such as name, address, transactional data, etc but often these must be manually queried and analysed to pull insights and carryout segmentation work which can be time-consuming.

A CDP allows for the centralisation of CRM data, Email, Ecommerce, loyalty programs & customer service data all into one platform to deliver a single customer view. The CDP provides a holistic view of all of these data points, allowing for better storage and data matching, built-in reporting and segmentation, predictive analytics, and automated activation across marketing platforms to deliver hyper-relevant customer experiences.

Complexities to consider before embarking on a journey with a CDP:

Whilst CDP’s can truly deliver much-improved customer experiences and as a result incremental sales/revenues, we must understand that they are rarely simple to implement.

One of the key challenges most brands face is having a deep understanding of their own data, how it’s collected, how it’s stored, and how well structured these data points are. Without this knowledge and good data foundation to build on top of, most CDP projects will fail. It’s absolutely critical to do the hard yards in creating effective data warehousing principles before embarking on your CDP journey.

Additionally, we must think about the skill sets required to identify the right business cases, Implement the solution within the business (including change management principles) & then to actually manage the utilisation of the platform day to day. Often these skill sets don’t exist and the skills required to manage each of the stages are completely different.

Choosing the right CDP:

So how do you go about choosing the right CDP for your brand? Firstly you must start with what you are trying to achieve, what is your overall vision for the future rather than just the problem at hand – this will help to ensure that whichever partner you chose your solution is future-proofed.

The decision should then be driven by the use cases you are looking to implement such as:

  1. How do I acquire more customers?
  2. How do I bring my offline customers online?
  3. How do I engage better with my current customers?
  4. How can I improve my customer retention rates?
  5. How can I use 1st party data to better drive efficiencies in marketing spend?
  6. How can I ensure that my strategy navigates the strict privacy boundaries effectively?

Each provider has their own USPs, whether that is their customer identity solution, ability to stitch data sources together, deep-dive analytical capabilities and predictive modelling or their ability to plug directly into activation platforms to deliver personalised campaigns & content. Linking your business challenges to these USPs will make the decision much simpler.

There is an argument about the cost of working with an outsourced partner and the expertise/resource that may be missing to build in house though. The ideal solution would be to work hand in hand with the tech provider to co-create a solution bespoke to your needs. This ensures that you retain ownership of the tool, have a much deeper understanding of how it works and ultimately a much higher likelihood of achieving the business objectives.

CDP’s can deliver fantastic customer experiences but do your homework and look at all the various options.

Whether you are looking to bring your offline customers online, stitch all of your customer data together, reactivate lapsed customers or deliver personalised and sequential messaging, a CDP can be a fantastic tool in your armoury for delivering better customer experiences and driving incremental revenue gains. It is critical however, to ensure that you first take the necessary time to define the overarching long term strategy and the individual use cases which solve your business problems.

You should also carry out the essential work on getting your customer data into a structured usable format – only once this is done should you embark on your CDP journey.

Supported by:

Data

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