In Jan 2020, Google officially announced that it will phase out third party cookies from Chrome.
Some unhappy with this move, did not see it as step towards addressing growing privacy concerns.
The 63% market share of Google Chrome might have been the reason for the buzz.
Whether it is controversial or a step towards addressing privacy concerns, this is going to be the reality and marketers have to adapt themselves for a "third party" cookie-less world.
We should also acknowledge that this is going to have a significant impact on the entire digital advertising ecosystem.
However, not all is lost.
You still have enough underutilized ammunition to power your marketing.
In fact, those are a lot more precise and not dependent on any third party.
I'm referring to your enterprise data.
We at Xerago, believe that Google's crackdown will only benefit brands like yours.
This is an eye opener for marketers who did not leverage or were underutilizing enterprise data.
Why would someone even collect data if they were not going to act on it?
With Google's announcement, they will now be rolling up their sleeves to transform the way they use enterprise data before the announcement comes into effect.
In this article, we will discuss:
- What is enterprise data / typical enterprise data that you may be collecting
- Where enterprise data can be used?
- Actionable plan to start leveraging your enterprise data
Enterprise data - What is it and where can you find it?
Enterprise data is any data that you collect from your audience (prospects and customers) directly or indirectly.
Data that your audience gives you explicitly by typing / selecting / writing are direct enterprise data.
Data that you gather from your audience without them directly providing it to you (analytics data for instance) are indirect enterprise data.
For simplicity, let us address both these as enterprise data.
Remember, enterprise data is not only data collected from your digital channels.
This also includes offline data that you collect through contests, events, etc.
Some enterprise data collection in itself is like doing a business with your audience.
For instance, you walk into a mall. Someone wants to give you a free sample of a new product that is being launched.
You share your contact details in exchange. Isn't this a business?
Similarly, you track your audience's behavior in your portal and in turn provide personalized and contextual communication. Win-win right?
Enterprise data offers you the opportunity to understand audience behavior, preferences and trends to provide personalized communication
Typical sources of enterprise data about your audience.
- Marketing websites: Name, email, phone number on subscription forms etc.
- Mobile Apps: Name, email, phone number, phone model, device ID, IMEI etc.
- POS: Purchased items, order value, payment mode, offers availed etc.
- Transaction websites: Access timestamp, transaction details etc.
- Surveys: Name, email, phone number, survey responses etc.
- Lead gen activities: Name, email, phone number etc.
- Contests: Name, email, phone number, contest type etc.
- Call centers: Caller name, customer id, Call timestamp, call duration, concerns with product, satisfaction level etc.
- Website cookies: Pages browsed, entry pages, exit page, session duration, number of visits etc.
- Social media: Social profile, first name, email address, comments, likes etc.
- Site / URL tags: Entry source, exit page etc.
- Email: Opens, clicks, conversion, un-subscription, bounces etc.
- Search, display and video ads: Exposures, clicks, conversions etc.
- Newsletters: Name, email, subscription, un-subscription, opens, clicks etc.
- Android and iOS app store: Download status, app version, comments, etc.
- Google business reviews: Name, comments
Some of these sources provide you with Personally Identifiable Data such as name, email, customer id etc. and some provide non PII data such as cookies, device ids, etc.
While integrating them may appear as a showstopper, there are readymade solutions that can help you with this.
What are the applications of enterprise data?
Enterprise data has a wide array of applications.
Currently you might be relying on third party service providers to reach out to segments that you want to target for your products.
With the third party cookie ban, this will become unavailable soon.
However, you can still use the enterprise data listed above to achieve the end goal i.e.) acquisition of new customers for your products.
How? We will come to that in a bit.
Before we even get into the applications of enterprise data, it is important to understand that these applications are possible only when you do two things correctly.
|You need to augment the ability to de-anonymize your audience and map identity between sources||You need to integrate data from disparate first party sources and activate this data to create a single view of your audience|
Here are ways enterprise data can be used in marketing.
Better targeting with accurate customer profiles:
Your audience interacts with you across multiple touchpoints.
Their profiles may look different depending on whether you look at data from one or many channels.
Only when you integrate their interactions across all of your channels, you can create a single view of your audience.
The customer profiles that you create after developing a single view of your audience will be relevant and representative of your customers.
You can further use these accurate profiles to source customers for your products and services.
This will also help you understand what inspires your audience to take action across different channels, devices and platforms.
Most marketers have already started to spruce their enterprise data collection efforts and its high time for you to get started if you haven’t already.
Hyper personalization is about delivering content that is highly contextual to the actions of a specific user.
Your audience is accustomed to hyper-personalized experiences from Netflix, Google, Amazon etc. and expect the same from other brands as well.
With enterprise data, you can be certain about the identity of the audience as well as their actions.
With this data, you can precisely map next best actions to them, thereby ensuring hyper personalization.
“ Marketers in 2020 have finally reached the 'tipping point' where scalable hyper-personalization of marketing activities is not only possible, but is rapidly becoming a requirement in order to stay up with evolving consumer trends.
Malcolm Gladwell, Author of “The Tipping Point”
Create customer journey maps:
You know that your customers hopscotch across channels.
When you start integrating first-party data from one touchpoint with other, you will discover how your audience consumes information at different channels before conversion.
Using this data, you can create omni channel customer journey maps and use the right channels at the right points and present highly-relevant information to influence and persuade your audience to conversion.
The benefits of interacting with your audience across multiple touchpoints are obvious.
Improve Omnichannel measurement:
Not everyone has mastered the art of measuring Omnichannel, especially when operated in isolation.
Following are several challenges that marketers face in measuring omnichannel efforts without an integrated enterprise data environment.
But, when you have relevant systems integrated and enterprise data organized, this becomes easy.
Contrary to the performance of channels in isolation, Omnichannel measurement might throw up some completely unexpected insights.
And these insights may have the potential to turn your marketing efforts upside down so much so that you may have to reprioritize your channels and communication across touchpoints.
Increase Attribution Accuracy:
One issue that marketers like you have struggled with for years is marketing attribution. According to Hubspot, marketing attribution is the second most important challenge that marketers face today.
Every channel owner managing your portal, display ads, email campaigns will claim attribution for success.
There are several attribution models available and different tools may provide a different attribution to each channel.
With an integrated enterprise data and every audience de-anonymized, attribution suddenly becomes simpler.
It becomes merely a function of any of the following attribution models you want to use.
- First-touch attribution: Attributes success to the first channel a user engaged with.
- Last-touch attribution: Attributes success to the last campaign a lead engaged with before converting.
- Multi-touch rule based attribution: Attributes success to the all of the touches along the buyer’s journey, based on a set of pre-defined rules.
- Multi-touch algorithmic attribution: Attributes success to all of the touches along the buyer’s journey, using an algorithmic approach that is based on a statistical model.
Actionable plan to start leveraging your enterprise data
But where do you start?
Don't worry. We’ve got this covered.
Before we proceed, there are a couple of pre-requisites for the effective utilization of enterprise data.
|Enterprise data utilization requires an organization-wide involvement and your teams can no longer operate in siloes||There is no single platform / solution that can directly help you leverage enterprise data and needs the integration of multiple solutions. You need to be ready for this journey|
Once you ensure this, you need to follow a few steps to start leveraging your enterprise data.
- Augment data collection: First and foremost, you need to collect as much data as possible from your audience. Here is where you have to scale from your default tracking codes and build custom tracking codes to track as much data as possible. The correct way to approach this is to visualize the end-state, list down what variables you would need to achieve the state and then customize tracking codes to track the identified variables.
- Aggregate and unify data: The next step is to aggregate all the data in a common place. You need to create data pipelines that can pull this data from disparate sources. Usually organizations would have a data lake or data warehouse in place. If you don’t have one, it is better to build it.
- Activate unified data with identity resolution: Once you have aggregated data from diverse sources, the next important step is to match the identity of the audience at each source. This is where Identity Management comes to the rescue. Remember, this is the most important step as the matching rates have a say on the relevance of the further action that you will take.
- Profile your audience: Now that you have established the identity of your audience, you will now have a clear picture of your audience's actions. Use it to create as many segments as possible. Customer Data Platforms come in handy here.
- Map omnichannel journeys: Once you have created segments and have a fair understanding of the preferences of each segment at each stage of the customer journey, the next step is to plot an Omnichannel journey map, where you define what content needs to be served on which channel and at what time. This is where marketing automation platforms will be of great help.
Do not start with creating complex journeys. Start with simple ones like the onboarding journey and scale gradually.
- Optimize efforts and attribute channels: Deploy journeys and keep testing them on a regular basis to optimize experiences at each touchpoint.
Understand how each touchpoint in a customer journey contributes towards conversion with the help of multichannel journey analytics. Bank on digital analytics tools offering diverse attribution models for this.
These are the key focus areas that differentiate a digital marketing leader from others.
Enterprise data is a key enabler for this and that's why this article is titled "Enterprise data – the gold mine of the future".
Remember mining your enterprise data requires extensive effort including technical expertise to integrate systems that don't have out-of-the-box connectors.
But at the end of the day, benefits outweigh efforts many a times, making it all worthwhile!