The days of succeeding with email campaigns while sending a generic message are done. No one disagrees with this point. Everyone sees response rates dropping. The answer? On this point, people in the know also agree: The answer is segmenting your audience and sending a targeted message. The debate approaches when discussing how to accomplish segmentation.
Much has been written recently on Account Based Marketing (ABM). Simple concept: determine as many attributes you can about your target accounts. Use those attributes to pick the best companies to reach out to. Great! This IS segmentation, however, there is a brilliant opportunity here, within reach, that is being overlooked.
The opportunity is segmenting your prospects (and clients) titles to more effectively target market with them. Again, no one disagrees that this should be done, but how is it currently being done?
Currently we see people building lists of 100’s (or more) phrases to match and segment. Example: “Marketing” OR “Marktg” OR “Mrktg”. These lists get long and have some inherent flaws:
- The lists are NOT comprehensive. Their will always be exceptions. There are some amazing, talented, consultants that have their “golden list” of match phrases like this. The problem is that you will need consultants to maintain and modify if you need changes. Not sustainable or efficient. This is a brute force approach.
- If you segment on a department like Marketing, you will miss the title level, such as VP. Conversely, if you segment on level, like VP, you miss the department. If you try to segment on both, now you have multiple lists of 100’s of phrases that again, it grows into the 1000’s if you want it to be comprehensive.
- Analyzing connected relationship becomes unmanageable. For example: Knowing that you have a VP of Marketing that influences two Directors of Marketing? You can’t establish this connection without multiple attributes that have been pre-calculated.
- Having a single attribute like Title Level OR Department makes the logic crazy complex. Trying to build a campaign that includes the “Top Marketing Contact”, “Top Sales Contact” and “Top Operations Contact” is only a dream when you only have a single segmentation bucket.
- It’s not fun. Complexity should be hidden and the average campaign manager should be able to set up brilliant campaign. Democratize it.
After 14 years of data mining and working with massive amounts of contact data, I’ll fast forward and give the answer: If you segment on both DEPARTMENT and TITLE LEVEL, you can accomplish, I’ll say it again, brilliant, segmented, campaigns that are easy to execute. Watch the video for a nice visual walk-through of the concepts.
“What is the first step to take to clean up your CRM data”?
Nearly everyone I pose this question to gets it wrong. The typical answer is “dedupe the CRM”.
This list was for a client: A stream of consciousness cut & paste from an email. He needed something to discuss with his team. He no longer believes dedupe (alone) will solve his data problems.
The real list is longer, but you only get that if you are my client.
- Silo Identification – Identify the sources of data.
- Structured Capture – Pool data from CRM, lists & databases.
- Unstructured Capture – Extract & Datamine. Email archives, etc.
- Data Assessment – Getting the facts about the data.
- Assessment Review –
- Consultation – blah blah
- Data Standards Plan – Design a strategy for future data standards.
- Data Normalize – Standardize according to Data Plan.
- URL Fill – Complete URL’s to disambiguate target objects.
- Data Mapping – Define and align data from all sources.
- Concatenate Silos – Combine into unified destination
- Duplicate Detection Rules -Define what constitutes a duplicate
- Resolution Plan –
- Scoring Plan – Develop weights for conflicting data sources
- Silo Merge – Merge data according to weights in scoring plan
- Automated Dedupe – auto
- Duplicate resolution – manual
- Data Actions – what happens w/ data
- Clean Review
- Address Correction
- Company Profiling
- Email Fill
- Enhancement Review
Do you remember your first time? I do. How could I forget? I was in love. The anticipation of being alone, just the two of us, was something I had been thinking about for weeks. When we all met our new team member, it was like every sales rep in the company was distracted. I couldn’t get any one-on-one time. Finally a holiday approached and I planned to be in the office, long after everyone had left. We would be alone.
The egg-nog was gone, the lights were dim and the office was empty. I opened up my browser and we were alone. Just the two of us: me and my salesforce.com
The first thing I noticed, my new love was unhappy. We had transferred all our data from a old Siebel CRM. My beautiful Salesforce was full of non-standard data and tons of duplicates.
So I took action. Here are the steps I took:
1. Develop a Normalization Plan.
(In the past I’ve called it a Data Plan), but the phrase has evolved. A Normalization Plan is a set of standards for your data. For example: for job titles, do you want them list verbose, such as “Vice President of Sales” or compact like “VP Sales”? Removing extraneous spaces and punctuation is also something to decide upon. Do you always go with “Incorporated” or “Inc”?
2. Normalize your CRM
Don’t even think about deduping your data before normalizing. This is a mistake of the uniformed. If a consultant wants to dive right in and dedupe, they are not skilled in the art of loving their CRM.
Dedupe without normalizing first is akin to putting underwear over your pants.
3. Pick your dupe matching rules
It’s got to be the right time and you must do some testing to make sure you’ve got it right. Use one of the tools from RingLead that provides customizable dedupe logic to match your business requirements. RingLead is a pro at removing Salesforce Duplicates.
4. Dedupe
It’s not the first step, it’s the last. When you really love your CRM you take care of everything else first. At this point, you’ll have a plan, you’ll know about all the little nuances and dedupe will be natural and successful.
What and when to automate and when to intervene is one of the most far reaching decisions you will make on the journey to a clean CRM. In fact, this automation vs. intervention decision quandary will impact all processes in your business. Instead of an in-depth how-to-clean your CRM tutorial, I thought I’d share some simple axioms that I base my decisions on when bringing efficiency and automation to a process.
#1 Don’t confuse automation with efficiency
Efficiency is how fast and how cheap a process can be done. Automation is applying non-human processes into a system. It is a subtle difference and that is why people get confused. For example: lead assignment can be automated, but if it is being done poorly or incorrect, it is not efficient. This is a natural lead in to #2.
#2. Never automate an unsuccessful process.
People can make mistakes, but to really screw up you need a computer. Make sure your processes work correctly, regardless of how fast. Once you have your process down, then apply automation.
#3. Automate a single process at a time.
There are exceptions and sometimes you can’t avoid doing a few things at once. The reason for this is immutably tied to #4.
#4. Measure what you automate.
Define what success is so that you can recognize it when it happens. When successful, automate something else and measure again.
#5 Complex systems are constantly redesigned
No one that I know can design a complex CRM system that stays 100% to the original design. Why do major software implementations fail and go over budget? Simple, the initial design did not encompass the complexities of the real world. Balance design with diving in and checking your premises. Be agile, be creative and get user feedback at critical milestones.
Duduping a CRM is like an equation waiting to be solved. Just like a high school math, the more variables you know the values for, the easier the problem is to solve and the more likely you will come up with the correct answer.
CRMs include is a vast number of “Data Markers”. These markers are a literal road map to filling in missing data. For example, if 100% of the emails for a particular company have the email format of Firstname.Lastname@domain.com, then you can probably fill in missing emails for other contacts with confidence. If you have the email domains for contacts, but the account record is lacking a website, that can be filled in too.
A company’s website address is a unique identifier. It is more important than the company name. Look at Peoplesoft as an example: long after the company was acquired by Oracle, you could navigate to www.peoplesoft.com. A few years later, it was totally absorbed…but the website did outlive the company.
Done properly, leveraging data markers within a CRM allows the properly trained consultant to pre-fill data for a more complete picture…BEFORE deduping. In addition the data should be standardized (sometimes called Normalized) before the dedupe process is done.
If you take the correct measures of: (1) data normalization and (2) data fill before deduping, your dedupe process will be greatly improved.
Some definitions:
Field: is a single value like a name, email, phone, date or note.
Record: is a set of fields.
In a spreadsheet, it might be row or column of data, depending upon the structure of the sheet. In a CRM, for example, a record could be an Account or Contact.
When fields are incomplete or become outdated, quite often, the record gets deleted. This happens in CRM’s, databases, Excel spreadsheets and in Market Automation Systems.
This is an error. Never delete records.
Why? Think of each field within a record as part of a math proof.
Like high school Geometry, the more given values you have, the better your chances to solve an equation. For example, if you only have a first name and email where does that leave you? Lets look at an example:
Starting data:
First name: Donato
email: donato@broadlook.com
What happens if we perform a “data proof”?
After each step, the new fields found are in RED.
Step 1: Is the email a free email provider like gmail, yahoo, etc? If not, fill in the company domain. The company domain is unique. Once you have it, there are many options to find and add more detail to your record. If you have an entire list of emails, I’ve included a video demo at the end of the blog that steps through the entire process.
After step 1, we have:
First name: Donato
email: donato@broadlook.com
domain: broadlook.com
Step 2: Is the website alive, if yes, visit is and fill in the company name
After step 2, we have:
First name: Donato
email: donato@broadlook.com
domain: broadlook.com
Company: Broadlook Technologies
Step 3: Extract contacts from the website. This can be done manually, but is much more efficient using automation. The Profiler can turn 60 minutes of research into a click of a button.
After step 3, we have:
First name: Donato
Last name: Diorio
Title: Founder & CEO
email: donato@broadlook.com
domain: broadlook.com
Company: Broadlook Technologies
Bio: Donato Diorio is a pioneer in the field of Internet research. As software architect and the owner of a top billing placement firm, Donato envisioned applications that could automate many of the most time-consuming research functions performed by his recruiters. With the assistance of a team of developers, Donato created a series of innovative tools that immediately impacted revenue for his firm…
All of the above could have been derived from an email only, we did not even need the first name. Additionally, we now have 10 additional contacts that could also be attached to the single contact.
So if you are thinking about deleting incomplete or outdated records in your CRM. DON’T DO IT!
So if you are thinking about deleting incomplete or outdated records in your CRM. DON’T DO IT! Your outdated and incomplete records contain wonderful possibilities. In addition, if you’ve tracked the source of where that original data came from such as a trade show or web form submssion, it makes it all more valuable.
Lastly is there any circumstance to ever delete a record? Yes, if no value exists in any field, nor can any value be extrapolated from it, then it can be deleted. Example: a few times a month, we get “Bill Gates” from Microsoft filling in a web form.
Here is a video that steps through the entire process:
Follow Donato Diorio on twitter: @idonato
