Three Key Obstacles Holding You Back from Creating the Data to Fuel Your Omnichannel Success

Here are the core data elements in a customer interactions table that are essential for supporting omnichannel analytics:

brand_name

geography_name

hcp_id (when available)

time_stamp

tactic_name

campaign_name

message_name

metric_name

metric_value

If you have this dataset in place, you're 80% of the way toward running marketing mix models, implementing next best action strategies, and conducting campaign effectiveness analytics. It seems simple enough, but many pharmaceutical companies struggle to establish this foundational table. The rest of this article outlines the key success factors that are often overlooked when integrating promotional activity data for omnichannel analytics.

1. Taking a Holistic View

Promotional activity is often executed in silos—Sales, DTC, and HCP marketing each focus on their own priorities and generate data in different formats. However, omnichannel analytics require integrating data across all these areas to answer key questions such as: How much Linear TV should be executed to fully support other DTC efforts like Paid Search? If HCP and Consumer Digital spend are reduced, how does that affect the performance of F2F sales efforts?

To support omnichannel effectively, it’s crucial to bring together all customer engagement data into a unified, consistent structure. Simply cramming different datasets into a table won’t work. The team building this data must focus on creating a single, integrated view that combines every data point—regardless of its source—so the analytics can deliver the insights needed to drive cross-channel strategies.

2. Setting Up Enterprise Naming Conventions and Hierarchies

Every brand leader seems to have their own unique names for marketing efforts. One may refer to it as DTC, while another calls it Consumer Marketing. And let’s not even start on the variation in tactic names. But if everyone uses different names for the same promotional activities, how can you compare the effectiveness of a tactic or channel across brands? How do you conduct brand portfolio optimization?

The answer: it takes a lot of manual effort to reconcile these differences, which significantly delays insights. Worse, the reconciliation process isn’t repeatable. What’s needed is a standardized, enterprise-wide naming and classification convention. This should be the first step when building out promotional activity data to support omnichannel analytics.

3. Providing the Necessary Context

What is the purpose of this tactic? How was a PDE (primary detail equivalent) or an ASP (Average Sales Price) calculated? Where did the data for this field originate? Which campaigns were executed using this tactic? These are just a few of the countless questions asked daily about promotional activity data. Is there a single document that answers all these questions? You likely already know the answer—there usually isn’t.

The only way to provide stakeholders with the context they need about the data is to build it in from the start. The data dictionary should include columns for definitions, synonyms, data lineage, example values, and points of contact for subject matter experts (SMEs). This information must be kept up to date and stored in a queryable format. It could be argued that the context surrounding your data fields and values is the real asset, as it makes the data usable and accessible for those who need it.

The Root Cause of Omnichannel Data Failures Lies in Experience, Not Technical Capabilities

Most companies have the technical capabilities to set up environments and load data regularly. The true challenge lies in the ability to see the big picture and leverage the experience required to define consistent hierarchies and provide the necessary context—something often missing in organizations where this type of data management is new.

Companies that don’t address these success factors often end up with a slightly improved version of their old systems, which ultimately fail to support the capabilities necessary for omnichannel success.

If you’re looking to overcome these challenges and set your omnichannel strategy up for success, reach out to our team of experts. We’ve created this data for dozens of brands, and we’d be happy to show you how SENTIER’s analytics-ready data solution and approach can set your organization up for omnichannel success.

Contact SENTIER today and let us show you how we can help you stay ahead.