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Susan DeMatei
 
May 20, 2014 | Analytics | Susan DeMatei

DATABASE SPRING CLEANING

What is it about Spring that makes one take on more challenges than is humanly possible?

Something about the warmer weather inspires us to fill our weekends with cleaning, our evenings with gardening and our workdays with new projects that we cheerfully start with enthusiasm but quickly fade into overwhelming exhaustion.

Don’t let your database health be one of the casualties of a well meaning annual tune up that gets back-burnered in favor or more pressing items.  It can easily be parsed into five steps that can be done in between the necessary Wine Club shipments, budget presentations, and email sends to perform a Database Spring Cleaning in no time.

Project One: Review Your Data Categories

Pull your database by category – whatever categories it is currently set up with.  Sometimes these categories were set up years ago by whoever built the database and they don’t apply anymore.  Sometimes they are current and relevant.  Sometimes neither you, or anyone at the winery, remember why it was set up that way and what the criteria was.  Whatever the case, it is good to look at the large “buckets” your database is is and re-evaluate at a high level if these still make sense.

  • Are your VIP groups still VIPs?  Based on what criteria?
  • Do you have overlapping “vague” segments like “newsletter”, “consumers” and ‘customers” that don’t  mean anything?
  • Do you have people that do need to be segregated, like “Trade”, “Press” or “Employees” separated out?
  • Is there a new channel, like a sponsorship partnership or tasting room addition, that added new people into the database that fell through the cracks and maybe aren’t in a category at all?

Remember, database categories at the highest level are meant to be helpful for you to pull queries and treat them differently.  If you don’t treat them differently, or don’t know what their criteria is, then you’re just creating busywork or confusion for the staff.

Don’t over-think it.  This exercise is more strategic that time-consuming.  Once you’ve put some thought into what the categories should be, it is usually easy to re categorize everyone.  Although you can have as many categories as you wish, I am a fan of less is more.  I’ve worked with dozen’s of winery databases, and haven’t seen many that require more than 3-7 customer groups.

Project Two: Combine duplicate records

We all have them.  No matter how many times we tell everyone to look up customer records before creating a new one, or ask our customers to login versus creating a new profile – we end up with duplicates.  Luckily, many of the databases we use have deduping tools built into them.  If your system does, you should looking at this every so often.  If your system doesn’t, a simple excel report will suffice.

  • Pull your customer database and sort by email and look for duplicates.
  • Then do the same with Last name, and first name.
  • Then finally do the same with address.

Assign someone in your staff to look through and merge the duplicate data records for a more complete customer life-time value and cleaner database.

Project Three: Remove unsubscribes with no purchase history

This could be controversial for some, but I believe in just deleting those prospects in your database that have unsubscribed without buying anything.  If you have a purchase record for this customer, you’ll want to save this record to have a historical account for that program and sales history.  But if they joined your database, never purchased, and then unsubscribed, they are someone who has changed their mind, for some reason or another, and doesn’t want to hear from you. Moreover, due to span laws you legally shouldn’t contact them, so I just delete them to be safe.

Note: if you collect sources for new prospects there might be value in keeping unsubscribes because you can see what sources yield good buyers and which ones do not.  But otherwise, these are just cluttering up your database.

Project Four: Clean up the Bounces

Bounces happen for several reasons.  There can be a typo in how it was entered.  The customer could have changed jobs or email clients and have a new address.  But did you also know that bounces are also caused by ‘out of office” replies and temporary burps in the system that happen all the time with large email servers?  Actually, being “too” clean can remove some good email addresses, so it is best to approach bounces with a bit of caution.

The first thing you’ll want to do is export your bounce list and clean up the obvious typos.  xxx@gmial.com or xxx@yahooccom, for example.

Then look at the number of times a contact has bounced.  If it is a singular and recent bounce and the address looks good, give it another email or two before you get concerned. If a repeat offender, it is likely what they call a “hard” bounce meaning it isn’t a true address.  For my clients, I pay special attention to purchasers and the Wine Club.  If it is someone who has purchased in the past or part of the Club, I usually call them and let them know their email is bouncing.  9 times out of 10 they update their email address.

For those who haven’t purchased, aren’t obvious typos, and are habitual bounces, you have three choices.  You either unsusbcribe them as listed in Project 3, you contact them and see if you can get an updated email address, or you contact an outside data house to perform a data append and see if you can purchase the updated address. (This is not as scary as it sounds and usually just requires you sending them the list of what you’re looking for and you pay about .30 a email address for whoever they can find.)

Project Five: Look for Patterns

This project isn’t really a part of Spring Cleaning, as your database is now pretty darn clean after performing these first four projects.  But in doing them, you’ll no doubt get closer to your customers’ behaviors and probably uncover some trends – so it is wise to be on the lookout for things all the while you’re performing these steps.  What customer groups are buying, opening email or unsubscribing are all helpful in planning out the next programs and getting smarter in your every day tasks.  The same way you find that missing earring when you move the couch, you’ll likely uncover some hidden insight when you clean your database as well!


While I recommend this progression (Projects 1-4 in order with 5 as a sort of over-arching thought), each of these project can be done independently and don’t have to overwhelm.  Granted, not everyone loves a good data-dive like I do, but it doesn’t have to be painful or or too time consuming.  And, if done periodically, it will keep your database in good health and responding well to your programs the rest of the year.

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