First to Zero, The Perfect Data Journey
We have seen zero, first, second and third-party data and are aware of their differences. Traditionally, marketers have used third-party data to gather customer insights, understand their needs and create personalised solutions. However, with the curtains coming down on third-party data aggregation and utilisation, marketers are forced to re-think their data collection and utilisation strategies. […]
Topics
We have seen zero, first, second and third-party data and are aware of their differences. Traditionally, marketers have used third-party data to gather customer insights, understand their needs and create personalised solutions. However, with the curtains coming down on third-party data aggregation and utilisation, marketers are forced to re-think their data collection and utilisation strategies. Both zero and first-party data are favourable with data protection and privacy laws and are hot favourites for merchants. No wonder formulating a strategy to collect and utilise zero and first-party data seems to be on every marketers’ to-do list.
Creating a Zero-Party Data Strategy
Zero party data gives marketers an explicit and exact description of what their customers want. Zero-party data is also dynamic – customers who are in control of the data provide information to marketers from time to time. This ensures that the data is always current and can be safely utilised by marketers to create customer solutions. The first step towards creating a zero-party data strategy lies in creating interactive content to engage customers. This can be done through gamification, making the customer data collection process seem like a fun task. Marketers can also make use of surveys, interactive engagement tools, emails and newsletters to collect information.
Creating a First-Party Data Strategy
Planning a journey with first-party data needs a plan that is simple and ensures high ROI. This can start with the following.
Create Inventory of Existing Data
As a marketer responsible for the data collected in the organisation, you must create an inventory of potential data points across different platforms. Leveraging data management platforms (DMPs) to help gather and organise all data sources. Bringing together all data points under one system enables a marketer to see a complete picture and improve service by understanding the customer mindset.
Map Data Needs
Marketers encounter several issues when using data to optimise ad performance — but data volume isn’t one of them. Quality and accuracy are the biggest challenges, as marketers see the importance of operating with the most accurate insights. Marketers must consult their CIOs to know what kind of data is given by input sources. Careful examination reveals that there is a lot more data available with marketers in their databases than what is pertinent to their business needs.
Data that is available isn’t always up for offer. Instead of jumping in to collect data, marketers must analyse the different types of data available and which ones will be. Mapping customer journeys and recording their interactions with every touchpoint of your business can also help determine your data needs in a focused manner.
Collecting Data
This is the most crucial part of your first-party data strategy. Collecting your customer data during registration is the best process andetting your customers to register on your website can involve using creative strategies. Collecting customer demographic data, behavioural data, customer click attributes are the other forms of data that will come naturally once a strategy is established. During data collection, efforts have to be made to ensure data collected is standardised throughout your organisation. Suppose there is a difference among your team about the specification or quality of data that they collect. In that case, it results in your first-party data being at risk for inaccuracy and inability to be used effectively.
Leverage Tech
Data collected has to be unified and visible to marketers in an organised manner. That will help in real-time monitoring processes, decide on the output level, and create suitable communication and troubleshooting strategies. This is achieved by using an open data framework where information can flow between multiple systems, such as from their website to their CRM system to customer support portals. A Customer Engagement Platform (CEP) can create comprehensive customer profiles drawn from multiple data sources and systems. CEPs can be utilised to analyse essential data from disparate sources so that marketers can draw precise conclusions about their customers’ preferences, effectively segment and target different audiences, and achieve scalable personalisation.
Conduct Tests, Measure Insights, Refine Campaigns.
Testing audiences and messaging your customers will ensure that your marketing campaigns are successful. Testing will ensure marketing campaigns are adjusted for customer reception before they are launched in a full-fledged manner. Discovering how specific audiences react to different campaigns and offers will help you as a marketer make more informed business decisions that drive results.
Marketers of all experience levels are ramping up on analytics education. Still, there is an opportunity to improve these skills. A study by a leading data tracking and analytics firm’s study says that while 73 per cent of marketers say they’re confident in their ability to apply data when personalising campaigns, only 67 per cent say they’re confident while analysing data. One in four managers say that they would like to have more skills to analyse data.
After creating a strategy, the next step undoubtedly is collecting data. How do marketers go about collecting first-party data? Let’s find out.
First-party data can be collected in a variety of ways. We take a look at some of the popular methods of data collection.
Also Read: Three, Two, One, Zero Data Liftoff
CRM Systems
Customer Relationship Management (CRM) platforms gather data about customers through their direct interactions with the merchant like email, phone, social media, website, or chat. Types of data that CRM collects include contact information (name, email, title), purchase history, lead source, customer interaction record, and more.
Data Management Platforms
A DMP can collect first-party data from various sources and segments based on characteristics like downloads, clicks, purchases, interests, or demographic information. DMPs collect data from multiple sources, such as cookies, IP addresses, device IDs, to help marketers target ads to the right customer segments. Organising data in a DMP can help marketers quickly overview their customer requirements and action immediately.
Pixel Trackers
Marketers are equipped to collect first-party data by adding tracking pixels to their website, product, or social media profiles that gather information about customer behaviours and actions.
When a visitor lands on the marketers’ website, engages with them on social media or posts or has a thorough look at their products and services, data can be collected and analysed to help inform business decisions.
Now that we are clear on collecting first-party data, it is essential to understand how to utilise it.
As mentioned earlier, first-party data is highly valuable compared to the other forms of customer data. Marketers may have various opinions about how it is utilised.
Compliance and Adhering to Data Protection and Privacy Laws
By far, the most important reason why marketers must begin working with first-party data. Various legislation across the globe governs the collection and processing of personal information from individuals who live in the European Union. As a marketer, the ownership of first-party data rests with you, getting your customers’ consent before collection and analysing that data rests upon you alone. It is deemed that first-party data has been collected legally and is free from encumbrances.
Gain Customer Insights
A marketer has to analyse the data it has collected and ensure it is centralised and available at all times. Analysing data helps a marketer to gain insights into their customers. Separate their needs from their wants and create optimum solutions. Analysis of online trends can throw insights into their customers’ likes and dislikes, the kind of content consumed, and what are the products they choose from your offing.
Also Read: Is AI Restyling Fashion?
Predict Purchase Trends and Personalise Campaigns
Careful analysis of first-party data tells marketers what their customers’ behaviour is and whether or not they are interested in a product or service, whether listed or merely advertised on a website. Basing on this, eye-catching campaigns can be created that are personalised so that the customer can be brought into the sales funnel. Data like demographics and other personalised information can help a marketer go ahead and create ad campaigns that are successful in driving up brand value and revenue.
Having understood how to use first-party data in marketing campaigns successfully, it’s imperative to have a quick understanding of the benefits of using first-party data.
Data collection in compliance with regulations.
Relevant optimised and accurate data quality.
Cost-effective option for marketers.
Moving away from third-party data and inculcating a habit of using first-party data only.
Parting Thought
Certain types of data have their strengths and weaknesses. A marketer cannot function with tunnel vision – wherein only a specific type of data is prioritised, and others are ignored. We have seen that zero, first, and second-party data is perhaps the best in terms of quality, but they limit marketers’ functioning due to their really small volume.
Third-party data, on the other hand, provides marketers with a bulk of data that helps marketers strategise and customise their offerings due to the sheer strength of numbers. Quality-wise third-party data leaves a lot to be desired and cannot be trusted as the sole source of customer data by marketers. The advantages and disadvantages of every type of data need to be kept in mind before working. As a marketer, one has to leverage the strength of each of these data types whenever the situation demands.
