How do you get ready to implement Lytics? Establish a Center of Excellence.

Customer-centricity works. One study found that every dollar invested in advanced personalization returns $20. 

That’s why you’re sold on customer data platforms (CDPs)—a single system that connects your downstream tools and centralizes your customer data. CDPs unify your customer data and send the right message to the right customer at the right time. With a CDP like Lytics, this means personalization based on intent, behavior, and in-depth customer profiles. 

So what does it take to set up a CDP solution like Lytics? How can you prepare your team to implement it? We suggest that companies implementing a CDP, like Lytics, follow these steps:

• Step 1: Decide how to organize your teams around your CDP.
• Step 2: Identify and pull in the critical team members.
• Step 3: Establish a Data Advocacy or Data Privacy Panel.
• Step 4: Develop a use case road map.

Step 1: Organize your teams around your CDP

Your first step is to think about how a CDP like Lytics would fit into your organization. This requires coordination across several teams, so you have to figure out who will be responsible for what. The critical questions to answer are:

• Who owns the customer data and data pipelines? For many companies, it’s owned by an IT or data team.
• Who is responsible for the governance, privacy, and security of customer data? IT often takes on this responsibility, with some help from a Legal team to manage privacy and compliance.
• Who is responsible for analyzing the data? Usually, an analytics or data science team is responsible for turning the data into actionable business insights (but see below for different models of how this might otherwise work). 
• Who owns the application of those insights into marketing initiatives? This could be a central marketing team or could fall to more specialized groups like your web team, ecommerce team, or others. 

Answering these questions is part of the transition process towards activating your data and creating personalized experiences that resonate with and delight your customers. Once you know who is involved and responsible for what, you can start to design a process for how each team works together.

Two common CDP operating models

Your CDP will centralize your customer data. Now, think about how your organization will access and use it. We have found two CDP operating models that are particularly effective. We call these the Center of Excellence model and the Matrix model. The core difference between them? Who is responsible for creating audience segments. 

The Center of Excellence model 

The Center of Excellence model is highly centralized. In this model, you create a core team of analytics experts who are responsible for all the data collection, organization, analysis, and insights your brand needs. This team would include your data scientists, analysts, and strategy gurus. In addition to being responsible for all the data handling, analysis, and insights—and they also would operate the CDP.

Their job is to interface with the CDP and use the data to inform marketing strategy, customer behavioral scores, and audience segments. They would then send briefs and audience segments to activation teams—for example, an email marketing team or a social media marketing team. These activation teams would then simply run campaigns based on the data they’ve been given. In this model, the evaluation of marketing effectiveness is also the responsibility of the centralized analytics team. KPIs encompass the entire customer lifecycle and may include lifetime value (LTV) and retention.

Pros: 

• This method creates a shared understanding of your customers and helps you deliver a coordinated strategy across the entire organization.
• You’re able to leverage insights from your analytics team and data scientists across the company.
• You have a smaller data footprint, which can minimize risk. 

Cons:

• Your activation teams will want more influence in creating the audiences to which they market.
• Your central data team’s lack of expertise in a specific marketing channel may mean less effective audience segments.

Matrix model

In comparison, the Matrix model is much more decentralized. In this scenario, an IT or data team sets up the CDP and connects it to your organization’s other tools—for example, Google Analytics, Facebook Ads analytics, and so on. 

But the actual analytics and strategy decisions are assigned to each of the activation teams. It is these teams who would be accessing and operating the CDP to create audience segments. For instance, the paid search advertising team and the social media team would have their own analytics team members who would analyze the CDP data that matters to them. From that, those teams would create audience segments and determine their campaign strategy. These same teams would also launch the campaigns.

In this model, evaluation of marketing campaigns also happens at the channel level. For example, the email marketing team may use KPIs that are relevant specifically to them, like open rates or clickthrough rates. 

Pros:

• Activation teams may enjoy that they have control over their entire campaign, from creating audience segments through to launch. 
• Activation team marketing professionals’ skills and expertise may be better suited for creating an effective strategy for their particular channel. 

Cons:

• Your company may not benefit from centralized intelligence or shared knowledge. Silos between marketing teams may continue to exist.
• There may be less of a coordinated strategy between marketing activation teams across the organization. Strategies may even conflict.
• This model creates a larger data footprint, which can increase risk.
• This model may not allow your company to leverage the expertise of data scientists or analytics experts as effectively.

How to choose the right CDP operating model

The Center of Excellence model typically works best for large organizations and those that are already highly centralized, as it’s best for leveraging your data science team and coordinating a company-wide marketing strategy. In our experience, this model also best fosters customer-centricity because the central data team can more effectively target customers as they move between channels. 

The Matrix model can often be effective in smaller organizations, particularly if you don’t have a dedicated analytics team or a centralized data warehouse. It’s also a good choice if you prefer that your activation teams create audience segments themselves. 

Step 2: Build your CDP implementation team

So who do you need to pull together to set up your CDP? Here are the roles we suggest you include on your team. 

• Key business decision-maker. This person is responsible for deciding which business goals the CDP will be used to achieve. They make final judgments on expected results and determine KPIs.
• Project manager. This person manages the CDP project, coordinates stakeholders, and sets deadlines. They are responsible for delivering the project on time and within budget.
• Development or IT team. These individuals are responsible for planning the data and implementing the code to set up the CDP and connect it with your data warehouse and any other necessary tools. 
• Activation teams. These are the teams that will use the data to run campaigns. These teams should be consulted as you set up your CDP and should have input on the data that you need to collect. 

Step 3: Set up a Data Advocacy Panel

We also recommend that you establish a Data Advocacy Panel (also called a Privacy Council or Data Council).

These individuals should be a cross-functional mix of people from across the organization. Their role is to create processes to manage your data, maximize privacy, and stay compliant with all applicable data protection laws.

Step 4: Develop your use case roadmap

We’ve seen that our most successful customers are those that start with a firm idea of how they want to use the CDP and its data, ideally with a tangible goal in mind. That’s why we recommend identifying a single use case to start—say, increasing conversions from web traffic or increasing email open rates. Starting with one clear application of your data helps focus the implementation of your CDP and rallies the team around that singular goal. 

Of course, it’s a good idea to think beyond that first use case, too. Our team at Lytics works with clients to identify several possible use cases and builds those into a future-ready roadmap. This helps you continue to drive value, one project at a time, as you scale up the use of your CDP across your company.

Investments now will create value later

Personalization isn’t just a trend in marketing—it’s the future. To provide the personalized experiences consumers want, you need to effectively use your customer data. A CDP like Lytics is a single source of truth, and it empowers you to unify, segment, and activate your data to send compelling marketing messages to the right audience segments — and to embrace customer- and data-centricity as an organization.

While it may take some planning to set up, we’re here for you. The Lytics team can guide you through the implementation pieces that need to be in place in order for you to make the most of your CDP, and explore how you can best use it.