The marketing industry often uses the terms omnichannel marketing and multi-channel marketing interchangeably. However, there are key differences between the two, which can fundamentally impact the way you build your marketing technology tool-set to complement an omnichannel or multi-channel personalization strategy.
Both are focused upon leveraging data, technology, skills, and processes to create an optimal customer experience across a variety of outbound and inbound marketing channels, and more specifically how those channels will be synchronized. The role of omnichannel marketing technologies and multi-channel marketing technologies is to help the marketer to automate their data and channels in a way that supports the strategy.
While multi-channel marketing is a discipline whereby a marketing department is delivering messages, offers and experiences to their customers across more than one marketing channel, omnichannel marketing is about throwing away the rule book and moving away from a core focus on the channels themselves, to instead focus on the most personalized and relevant offer or experience to a customer, regardless of the channel or channels. Confused? Ok, well let’s look at it in a little more detail…
How does omnichannel marketing differ from multi-channel marketing?
Gartner defines omnichannel marketing as “the seamless integration of digital and physical assets”, and according to Forrester, “a truly omnichannel operation that spans the customer lifecycle will optimize revenue, deliver capital efficiencies such as cost savings, spawn operational efficiencies, and improve the customer experience overall”.
At BlueVenn, we have created an omnichannel marketing and CDP solution, based on the interpretations of hundreds of marketing leaders, with the belief that this type of marketing is about putting the customer at the heart of a strategy, which ensuring that, regardless of the channel or channels through which the customer chooses to interact with a brand, the message, campaign or offer they see is always consistent and personalized.
Although marketing technology capabilities have improved significantly over time, the very nature of using many different tools and databases to deliver marketing communications (email, SMS, mobile, etc.) creates a state of channel-focused marketing with many siloed campaign decisions. Since each channel requires its own automated workflows and databases to deliver a message on that channel, the platforms do not traditionally support each other to deliver the “seamless” experience that an omnichannel strategy demands.
Multi-channel marketing also focuses on interacting with customers across multiple online and offline channels, including mobile, social, in-store and direct mail. However, the crucial difference between omnichannel marketing and multi-channel marketing is that the former delivers one consistent message wherever the customer goes, while with the latter, the brand and channel is the focus, but not necessarily seamless. The lack of integration between channels in a multi-channel marketing strategy can lead to impersonal or conflicting offers and experiences, which can be a turn-off to customers.
For example, with an omnichannel customer experience, a customer may see a post on a brand’s Instagram account for a pair of pajamas, leading them to then visit the website to find out more about the product. While browsing on their desktop, they add the pajamas to their basket in an eCommerce channel, but don’t complete the purchase. As a result, the brand sends them an email channel reminder prompting them to purchase the pajamas while they are still in stock, so the customer opens the mobile app, to find the same pajamas and cart history synced to the mobile app cart, and completes the purchase.
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- Unifying data to create a Single Customer View.
- Unifying cross-channel decisions with customer analytics, segmentation and RFV modeling.
- Adopting machine learning and Next Best Action.
- Omnichannel customer journey orchestration.
- Multi-touch attribution and channel optimization.
However, with multi-channel marketing, a customer may see the same image of pajamas on the brand’s Instagram account, browse them on their desktop and add them to their basket, only to later receive an email about a different, unrelated product. If they think about their chosen pajamas again, which the customer might not actually do without the cart abandonment reminder, on opening the app they will find that their basket is empty and need to start again. They’ll have to make the effort to go back on the desktop to complete the purchase, or perhaps will not bother.
In other words, omnichannel marketing, unlike multi-channel marketing, provides a seamless customer experience, with every channel supporting the other to continue the same customer journey, and ultimately working towards securing the conversion.
Omnichannel and multi-channel technology layers
We break down common technology stacks into 3 simple layers:
- The Data Layer
The Data Layer refers to the fact that each channel system you invest in, whether that be an ESP, SMS, mobile marketing, DMP, social, eCommerce or personalization platform, to name a few, will each have their own underlying database, which will be optimized for that channel platform. The ESP will need to store email addresses, the SMS tool will need cell numbers, etc. - The Decision Layer
The Decision Layer refers to the fact that each of those channel solutions will also include some form of workflow or marketing automation, to be able to make decisions about a campaign audience and schedule a frequency/time to deliver a message or sequence of messages. - The Execution Layer
The Execution Layer refers to the fact that once you have made your decisions and scheduled your communications, using the available data, you can then execute a message, offer or promotion through that channel.
In the diagram below we have summarized these 3 layers into 4 columns, named ‘Siloed’, ‘Data Hub’, ‘CDP/SCV’ and ‘X1X’.
Each of these columns visually summarizes how marketing technologies are commonly being used by organizations, and illustrates how an X1X technology stack fully supports an omnichannel or multi-channel marketing strategy effectively. This is a fundamentally different way to think about your data and technology needs. Let's explore these 4 columns in a bit more depth...
The 'siloed' marketing approach
In the Siloed method, all of your channel solutions are operating in silo from one another, which means you'll have fragments of data about your customers held across many disconnected databases, thus you have no single data source to rely upon to give you an accurate, omnichannel or multi-channel view of how a customer interacts with your brand. In the 'Data Layer' this is represented by 4 databases (perhaps these are the underlying databases for an ESP, SMS, CRM and a mobile marketing platform).
In the 'Decision Layer', the marketing team(s) will be duplicating their campaign decisions across the variety of channel tools within the business. The call center makes a decision based on what they see in their CRM, the email marketing team will create decisions about audiences and the scheduling of email campaigns within the ESP, the eCommerce team is optimizing how customers are pushed through the website, and the direct mail team is making further decisions for when the catalog should drop. Essentially, the marketing function is making Siloed decisions channel-by-channel.
And finally, in the 'Execution Layer', each channel will then send out a communication or series of communications, which can be executed/activated in the same Siloed way. The resulting data and conversions get logged back in the siloed databases, and then we begin again.
This is still a fairly typical setup for many organizations, when executives from different departments and divisions of an organization bring on new technologies to focus on individual requirements, but does not support omnichannel marketing or multi-channel marketing strategies without a lot of hard labor to extract and move data between systems, or perform one-off projects to extract and load data from one system to another. A lack of joined up CX strategy can lead to this type of technology adoption, which wastes resource and requires manual intervention from IT or other departments to keep the technology plates spinning effectively. These organizations have no single unified view of their customers, cannot synchronize a campaign across more than one channel seamlessly, and are duplicating a lot of effort for each campaign.
The 'Data Hub' marketing approach
The Data Hub approach relies upon a lot of ETL (Extract, Transform and Load) processes. This can be automated using ETL tools or home-grown solutions or can be a manual process undertaken by a technical department or 3rd party. Essentially, whether automated or manual, this process is to extract data out from one system, transform it into a structure that another system will accept, and then load the data into another tool (or perhaps even load it back into the same platform after the transformation of the data has been performed). This starts to create some form of synchronization of the data across the different channels, starting to break down some of the siloes in the Data Layer and can therefore be an effective way to enable your customer data to support a multi-channel marketing strategy.
When a person or department is performing the ETL processes manually, they would be extracting data from one system before analyzing, cleansing and appending it, preparing the data to be uploaded to another system, and then performing the load of the data. This pulls fragments of customer information together to support a better multi-channel decision in the Decision Layer, based on a wider set of data and variables. In turn, marketers can then create more refined audiences (for example, by using ETL to push a lifetime value calculation from an eCommerce system into the ESP.) The marketing team can then start to segment an email communication by the customers' LTV and loyalty more easily.
An ETL platform will, however, automate the extraction, transformation and loading process to reduce the need for using dedicated resources to perform the same tasks. This is not going to support an omnichannel marketing strategy, however, because your Decision Layer and Execution Layer remain siloed within many channel platforms. Equally, although you are pushing data between your systems’ databases to start to remove some of the siloes in your Data Layer, none of those databases is providing marketing with access to one single source of unified data to see, analyze and activate all the data points from all channels.
The 'CDP/SCV' marketing approach
In case you are wondering, CDP is the acronym for a ‘Customer Data Platform’ and SCV is an acronym for 'Single Customer View'.
You can explore the definition of a CDP here, but in the context of our illustration, the CDP technique is less about pushing data between systems like in the 'Data Hub' method (it does do that too), but more about replicating the data from all the systems and then unifying all the customer data in the Data Layer into an SCV. So, the data still resides in the source databases in the Data Layer, but when replicated to the Single Customer View, all the customer data fragments are merged into unified customer profiles using identity resolution, which may also cleanse, append, and transform the data too when data quality is an issue.
The key thing here is that this can start to enable your omnichannel marketing strategy because you’ll be able to know everything about a single customer, including the channels they are most active on, how they move between channels, and also which offers and communications have historically worked best. The CDP/SCV approach also enables modelling and analytics to be applied, and furthermore that data is then persistent over time, so that this SCV continues to build up over time and becomes more robust each time an interaction occurs.
This then can output the unified customer profiles to each of your channel platforms so that you can then schedule campaigns for each channel in the Decision Layer using a consistent view of the data. You will still be making siloed decisions, so it's only going to fully support a multi-channel marketing strategy, but it does mean that you can make more meaningful multichannel decisions. For example, choosing to exclude customers from an email campaign audience because you'll have more knowledge about whether to include them or not. You may also have knowledge in your email tool of when they last interacted on other channels, helping to make decisions based on how customers interact across other channels.
In the 'CDP/SCV' method, the Execution Layer remains siloed, but if your marketing strategy is evolving from a siloed strategy to a multi-channel strategy, then the CDP/SCV approach is where marketers should be focused, as a Customer Data Platform can help massively to achieve that by creating a Single Customer View and removing manual methods of ETL.
The 'X1X' marketing approach
X = Unlimited data sources, 1 = One decision, X = Unlimited channels.
X1X goes one step further than the 'CDP/SCV' approach, and is the best approach for an omnichannel marketing strategy. Not only does it unify all the customer interactions in the Data Layer into a Single Customer View, but it also, importantly, unifies the siloed scheduling and decision-making in the Decision Layer, to create one single point of control for every inbound and outbound channel.
Rather than using automation and workflows across the ESP, SMS, mobile and direct mail channels, you have one place to make decisions that are inclusive of all the channels. This enables you to create one audience and offer, split that audience along specific channel and offer pathways, and even trigger a sequence of multiple channels to support each other. Data can be pushed from channel to channel, an email click could trigger an SMS, a cart abandonment on the website could trigger a mobile push notification, etc.
This X1X method removes the siloed decision-making process and tells all your channel solutions when, how and who to send communications to. With all the data points available, having unified all the data in the same way as the CDP/SCV method, X1X also allows you to split a customer journey or campaign along many paths and channels, bring in personalization data points beyond those you could before, and then ensure that activation occurs seamlessly, with each channel able to support and synchronize with the other.
The added benefit of the X1X approach is that as you add new databases into the Data Layer over time, or add new emerging marketing channels as they become available, they can just be plugged into the single Decision Layer, either at the Data Layer or the Execution Layer end without disrupting the omnichannel strategy, and prevent siloed data, decisions and execution becoming an ongoing issue later down the line; essentially future proofing your marketing stack and investments!
Finally, X1X enables household brands and businesses with a lot of heritage and older, antiquated database systems to use this framework and help them move along their marketing and digital transformations. The beauty of the X1X approach is that it also does not require an organization to replace the existing technologies they are already using. The X1X approach should be agnostic to whichever systems you already use, essentially transforming siloed channel solutions into omnichannel data sources and omnichannel end points.
If you'd like to find out more about this X1X technology approach to omnichannel marketing then please get in touch with BlueVenn. X1X is our own unique framework, built up over time, and our team of experienced and knowledgeable consultants can discuss your existing technology setup and strategies, and walk you through a demonstration of the platform if desired.
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