"Dirty Data" is just not sexy...or is it?

We have all been inspired by success stories regarding the digital age of business: its power to supercharge attracting new business, converting people from suspects to prospects and then serving these new customers until they become raving fans. But how do we do it?

The potential for your business to realise even a shred of the digital promise is a back to basics exercise focused on your data.

This is an exploration on how you can get your business data in one spot, categorise this data so it makes sense and then kick off automation processes that have a credible impact on a prospect or customers level of engagement.

1. Build a single source of the truth. Get everything in one spot.

Get every single piece of business data in the one spot. Even if you have different tools for lead generation, sales management, order processing and finance, start investing in technology that will allow your business to achieve a  single source of the truth.

  • Invest in technology that can easily integrate
  • Unite the front and back office by connecting your finance tools to your customer management tool set
  • Document the entire lifecycle of a customer. Map where their information sits at every stage and build a plan to consolidate this information
How can we track a single customers lead source, conversion time, revenue achieved, cost of acquisition, customer satisfaction score and any referral information in one spot?

2. Clean your data! Scrub, spit and polish.

Not all data is created equal and businesses often forget that data often needs to be cleaned to be truly useful. Small businesses are energetic, fast growing places and are focused on attracting new customers and serving these new customers well. No one has time for clean data! But now that you have all your data in one place this should now be easier to manage. There are two key ways to tackle dirty data:

1. Don't let bad data in

  • Train your staff to value clean data - demonstrate why clean data will save them time and help them serve their customers
  • Utilise default fields and data validation in your database - protect data's integrity as it is entered
  • Measure and track data cleanliness then reward your team for clean data

      2. Clean up the mess

      • Make changes to the way you store and order your data - I call this fixing the data model - many of my previous customers put this off for too long slowing their business down and making it impossible to automate
      • Spend money on cleaning your data - hire a consultant to scrub, spit and polish your database

      3. Categorise. Tag, label and group.

      Now we have all of our data in one spot and it’s clean. We’re ready to categorise this information so we can be relevant, unexpected and engaging. Tag, label and group your data into meaningful buckets:

      • Dates and Timeframes: Use dates and timeframes to categorise your database. All good customer management systems have date and time stamps on any action or activity logged. Use these dates and timeframes to create meaningful engagement along the customers journey
      • Status: Use statuses of prospects and opportunities to guide your customer through a process and engage them with relevant and targeted information e.g Not Ready to Proceed +6 months.
      • Tags and Labels: Create meaningful tags and labels to sort your customers so you can target them with meaningful content to assist with conversation or promote referral or repeat business.

      Your data is in one spot, clean and is in meaningful buckets. You are now ready to design customer engagement.

      Next week I am going to bring some ideas to the table around effective customer engagement through automation.

      Now go on get started fixing your "Dirty Data" :)

      © Andrew Sloan and "Andrew's Blog", 2015. Unauthorized use and/or duplication of this material without express and written permission from this blog’s author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Andrew Sloan and "Andrew's Blog" with appropriate and specific direction to the original content via www.andrewsloan.com.au