Today’s marketing is data-driven. Since the marketing went digital B2B Publisher could able to measure the real impact on revenue. From acquiring a lead to converting it into a customer – all the marketer needs accurate data.
Publisher capture data from leads for every stage of the funnel – and with every shift of buying behaviour. But it is not just required to capture the data but building a database that fuels the revenue generation process.
We asked some publisher that – ‘Do they have data infrastructure to support brands revenue goal?’
The answer wasn’t satisfying. Most of the publisher does have data – but they don’t have the data infrastructure.
In this blog post, we will learn how a publisher can build the data infrastructure so they could support the revenue goal.
Being a Data-driven is a culture:
Building a data infrastructure starts with the people.
It is important to train marketers to build and work for data infrastructure.
A data-driven culture promotes analysing activities for every department of marketing. Marketing involves designing, coding, content, and analysing work. Publishers have an in-house stack for every individual operation. A true data-driven culture is well integrated and all of its operations are aligned to each other following strict data security and compliances.
Landing page designing:
Landing page development is one of the important activity many marketers overlook. With a data-driven approach, one can test multiple formats with the audience to measure their response and engagement. While testing the formats LP team must capture the results and data – sorting by type of campaigns and industries.
How the LP team help to build data-infrastructure?
Marketers know the audience is diverse. Personalisation is a key factor to engage a diverse audience and push them down to the funnel. Landing page personalization for campaign type and industries enables the marketer to map the accurate data responses. It is crucial to have a data guy or a system in the LP team who manages and analyse the sender and receiver end data to update the database with the same. The data can be used on ongoing or future campaign with the help of AI data modelling to identify the best responses pattern.
Content is data work. In business, it is not enough to create content but a content that is a data-driven. Various intent signals from the audience can affect the content creation and personalization for good. Talking about the publisher, B2B Publisher has to adjust or personalize the content to conduct various test and campaigns. The content changes with data must have to note in the database.
By now all sizes of companies use automation. Email automation technology is old for marketers. Email automation helps marketers to boost operation efficiency so they could increase revenue acceleration. The large part of data infrastructure is involved in email automation – to streamline, personalise and nurture the audience.
A right automation tools and technology is an advantage to build an effective and actionable data infrastructure. Marketers along with focusing on other marketing task and its part in data-infrastructure have to focus on email automation – to glean 1st party intent data, later in the bottom of the funnel nurturing it helps to increase the conversion rate.
Lead verification and updates:
Lead verification is done by the manual and automatic way. Like APSS Media leverages its LIByAI tool to analyse the data with the help of AI as well as two-layer verification with skilled data persons – B2B Publisher must continuously be productive at verifying the data incoming and later update the infrastructure with it.
The Garbage Out Approach:
It is a lot easier to filter out bad data from the beginning. Garbage in and Garbage out is a familiar concept in computer and mathematics. The marketer can use it to build a healthy database. It goes like – If you don’t allow bad data in your data infrastructure It will be easier to build and maintain a database.
B2B Publisher faces data duplication and contacts missing issues. To address it data quality team must be on to search whether they have contact data missing of prospects – If have then research team must be on to find and fill the missing contact details.
Some tactics to adopt garbage out approach:
Finding out missing contact information:
As mentioned above – There must be a Research Department to solve missing contact information issues. The research team must be integrated with another department as email automation and Landing page team to keep them updated with the latest data of a lead or prospect.
This way marketers just not update the current data infrastructure but flush out bad data from the database.
(Here are some data cleaning tools and sources that save your time and budget:)
Finding out duplicate data:
When the publisher delivers the campaign they may get the same lead repeated one or more time. This can arise issues of having many duplicate leads in the database. A strong data infrastructure is clean and never entertain bad data. That’s why you should always ask your team to identify those repeated leads.
Some criteria you may apply to filter out those leads from the database:
- Duplicate email address.
- Duplicate First name and Last name combined.
Finding out outdated leads:
While running a campaign out team often jokingly say that – ‘Leads are not a tree so they can move.’ This is true. Some leads are agile they move from one department to another in no time. The DMU might go a random change in hierarchy. Some new Decision makers or leads can enter the DMU and some may leave.
It is important to ask questions like – ‘Does your marketing team keep an eye on lead’s, including changing department and account time to time?’
Once interested lead can be outdated, as it switches through Job title, job level and department within the account or from account to account. It is Publisher’s job to Identify them and segment them right.
This tactic makes data infrastructure strong and healthy.
Publishers can build effective data infrastructure and by leveraging it the leads can be prioritised by its readiness to buy. This way help reduce cost per lead resulting in higher ROI.