The value of Contact data. Part 1: Overview
One of the first obvious but still often overseen facts about contact data is, that this data only represents
- a person’s details
- from a specific perspective and
- for a specific purpose
To better explain this important insight:
If you store a contact e.g. in your CRM, you will probably store data like first name, last name, address, phone, e-mail-address etc.
Typically you will save the data of the person’s business address. And probably the address of the physical business location of that person. And you do that, because your CRM implicitly defines which data is relevant for the business usage of this contact.
What does that mean?
Basically it means, that you know almost nothing about the contact and that you only have very limited options to use this data. But why is that?
Contact data vs. digital identities
CRM contact data is gathered to support acquisition.
It requires another perspective than e.g. contact data for social profiles, which might only represent selected data to gather career relevant information. Or a more personal bio as a hook for content of the person’s interest like on Twitter. Or contact data relevant for newsletter subscriptions.
The use case decides which data of a contact you need and how you can use it.
Understanding contact data
To really be able to make business with other people, you must understand who is behind the contact data.
It is a difference to deal with people privately or in business. Even with some of your private friends you will find out, that their business profiles do not match their private profiles at all. Still both profiles are valid, they are bound to the same person. But they are bound to a different context and role, too.
Taking this into account I come to another point that is probably obvious, even so nobody takes corrective actions:
One contact might have multiple profiles
If data is entered into a CRM system, it is entered from the perspective of the relationship owner. So if for example a sales person enters the data, he does that from his perspective. The classification will represent his view.
This leads to the effect, that his thoughts about the networking value of this contact will influence your organization’s behavior on that contact.
It is very likely, that more than one person of your organization will deal with the same contact. But typically they will just check in the CRM, if there is an address in the system, but not if the entered data does represent their view about the contact profile.
In almost 30 years of dealing with contact data, I have not found a single organization that managed separate profiles for the same contact. And I rarely found organizations that managed profiles that allowed multiple people to qualify, classify or describe a contact from individual perspectives.
This does not only lead to a poor and incomplete picture of the contact, the worst thing from a company’s perspective is:
Your CRM data is almost useless.
Social network connections are done between two people – and not between your company and the other person. Quite often you will find out, that social networking contacts never have been entered in your CRM system. So, if your employee leaves, the potential networking partner disappears and the company will loose the complete potential without even noticing it.
In practice this means: You paid your staff to establish social connections and business potential for your ex-employees next job.
But how can you do better? Read on!
After you have entered valid contact data into your CRM system based on e.g. a business card of a contact, you are probably on the safe side for a certain time.
If you double check this data with social profiles, you will find out, that it is hard to validate data, because the social profiles of the same contact need not be up to date or they are different by intention.
In social networks like LinkedIn or XING you will often find private e-mail-addresses instead of business e-mail-addresses, if you are not dealing with somebody who represents a sales person. Even phone numbers or topics of interest, titles and sometimes even company attributes do not match. Still, the data might be valid. You never know who runs a private business asides his official job.
In the end the best way is to have all identities managed in one contact profile. But this is still not enough.
To really get a relevant picture about contacts, you need identities PLUS communications, roles and relations in one single place. And this is basically what social CRM systems try to achieve.
Contact data vs. people profile data
Depending on the contact source e.g. Twitter you might know very few contact details – but you probably know the contact better than your sales, because you know parts of his interest profile.
If you track your contact’s interest groups on social networks, his interests published by himself and his “likes” and “re-tweets” or recommendations, you get a people profile for a part aspect of that person that most probably exceeds what your CRM probably can tell.
Contact data is good to locate a person physically for a specific use case. Social profile data often represents a career-optimized view of a persons profile. But behavior in social networks, blog posts, publications etc. tells you a lot about a person’s people profile.
Contact data represents real persons
This seems more than clear at first glance, but let us take a deeper look:
What about all this contact data that is not bound to a real person? We all know those team-inboxes, group call numbers, hotline numbers etc. Can we ignore them?
No, we can not. These virtual groups or representations are the single point of contact for specific topics – and even they can have multiple identities. Example: Just think about [email protected] and http://support.company.com and @support (Twitter). This list could go on…
If parts of this data change, everybody who relies on this information must be sure, that the CRM system stays a valid source of data. A one-stop shop for consistent information.
Ok, but why do we have to care about that?
Because we have to manage CHANGE in our CRM systems. Real persons change, too. Within the same company, from one company to another company and sometimes they even change their names by marriage. And even worse: In social networks some people cannot be properly identified by their virtual identities, because the identities might not match the physical person behind them.
It is really hard to track and maintain a contact’s data, identities, profiles, roles and communications today!
This means, that we need processes and tools that help us identify and manage changes on all data in all profiles and roles. In less time. With a growing number of profiles and data. But with less staff and less capacity.
So, why don’t we just merge the data from all sources together?
Why xRM is not enough – unmergeablity of data
It is because of another insight that is not obvious at first glance:
If you think, you can just dump data from all sources to an Excel sheet and merge the data to get a full view of your contact, you will get disappointed. And you will not need much time to find out, that you cannot merge the date in one line, as the data has dimensions and relations.
To explain that, I make some examples:
Scenario 1: Create an Excel sheet. If you add a column for each attribute you find in your data sources, this will result in a huge sheet. So reduce similar columns that have the same content but a different name like “1stname”, “Firstname” and “First name” to one column. If you find out, that a person can have up to 7 e-mail-addresses, add 7 columns for e-mail-addresses. Now import the data.
I bet, the result will show a lot of “whitespaces” which means, that there are a lot of lines in the sheet where only few cells are populated with data, because some contacts might have less than 7 e-mail-addresses.
Reason 1: Such data structures will increase software complexity to handle automation, because your automation software will run into whitespaces where it expects data – or it gets difficult or impossible to choose the right data column.
Scenario 2: Create an Excel sheet and provide just one cell per attribute. For each contact, fill all e-mail-adresses of a contact into the same Excel cell. That will solve the whitespace problem, if a contact has one e-mail-adress only.
Reason 2: You will have the same problem as above. Software will not be able to use this information for automation without adding software complexity.
Is your CRM the solution?
Instead of collecting all data in an Excel sheet, you could use your CRM system to gather all contact information in one place.
Reason 3: You will find out, that your current needs require a very different structure from what you have in your CRM system. A whole lot of companies invented CRM systems around five to seven years ago and jumped on the xRM train to master data relations.
The insight is: Our former approaches with xRM solved the problem to have all CRM relevant data in one place.But today xRM is not enough.
Social media requires us to reconsider the split of marketing and sales. CRM must become Customer Lifecycle Management (CLM). And the people that work with these systems must become hybrid experts for marketing, sales and customer service.
CLM integrates the whole process chain from inbound marketing over xRM to customer service management. And the center of this process is the contact with all its identities, profiles, roles, social interactions and social communications.
Mastering contact data management is an art. And it is not becoming easier with all those digital identities. To get a full picture about a contact and to manage contact data properly, you must define your relevant and inevitable use cases on contact data.
Use cases and context drive the attributes and relations you need. And this drives the requirements for your tool chain and the process integration in a CLM world. But at first instance it is a challenge for your contact data model.
If you are interested in good practice, I had about 30 years of time to gather experience. There might be some useful stuff in my brain for your company, too.
Wow! You mastered Part 1: Overview! This was a heard lesson, but i hope you still enjoyed the wild ride.
What will come up next:
Part 2: Good practice for CRM contact data structures
Part 3: Good practice for non CRM contact data structures
Part 4: Tools to master contact data
Part 5: How to enrich contact data for targeted campaigns