8/10 Problems with your Analytics is your Data.

“A man with a watch knows what time it is. A man with two watches is never sure.”

Segal’s Law

Segal’s Law is an adage that illuminates the potential pitfalls of having too much potentially conflicting information when making a decision.

Certainly, one of the things Analysts like me love about the world today is just how many systems and data there is available to help us to improve processes via analytics.

But this is also one of the biggest problems for decision-makers. The sheer volume of data that is produced by every interaction by every one of the applications we use every day can make it difficult to decide on what holds the greatest value for us.

As such, there’s a lot of potential for noise and distraction from what should probably have your attention. It’s a problem that affects almost every business, but in this instance, I’m going to discuss the problem with data in the sales-marketing department or workflow.

Point 1: Where the Data Problem Starts

Think about how many different software applications you use in an end-to-end process. For the sales-marketing-accounting example, you probably have:

Marketing Platforms: Including a Website/ eCommerce site like WordPress. Social media platforms push your free and sponsored content or advertising. You may also use messaging tools like Intercom for online chat, SMS and emailing applications like Mailchimp in your marketing mix.

Engagement metrics like Leadfeeder, Hotjar and Google Analytics tell you important information about who’s visiting particular webpages, when, and how they got to your website.

CRM/ERP: Although integration is possible, most organizations have different enterprise systems for sales and marketing, and the accounting solution used to process payments and other accounting processes.

No wonder Experian found that only 24% of companies state that they have a single customer view! Every one of these applications provides masses of data across a component of the customer journey.

Feeling fuzzy about your direction?!

This makes it hard to know what you should be focused on, how your sales and marketing function could be optimized to improve revenue generation and/or to save costs.

To make things more complicated, each system may have different data hierarchies or minimum data requirements. If these don’t match, you’re likely to experience issues with reporting, integration. This even makes it difficult to assess how good or bad your master data health may be!

Point 2: Manual Reporting or Compiling Sales & Marketing Reports

Most Sales and Marketing Executives will literally lock themselves away from all other matters to manually compile monthly reports. And nine times out of ten, they’re using Excel ….are you guilty?

Not only does this render teams without a leader, but it’s an inefficient and inaccurate process. Bringing data together in Excel allows human error to creep in as individuals modify reports. (Sometimes people even fudge the numbers a little to make reports look more favourable).

Four things here should be highlighted.

  1. Excel is not a database. There are many different examples of where the improper use of Excel has brought a business or project into question.
  2. The sales-marketing strategy is something that can make or break your business, so you can’t afford to get it wrong.
  3. Without analytic from a dedicated database of cleansed, standardised integrated data, you won’t have a good grasp of the end-to-end marketing process.
  4. Executives – confused by noise, duplicate records and gaps in information – will continue to waste time on inaccurate reports that are out of date by the time you complete them.

Clarity on your business growth strategies Analytics in this space can put you on a path to more rev gen’ or save massive amounts of overspend in other areas. A small investment in BI will easily deliver positive ROI within 12 months.

Okay, so “How to fix It, Save Time on Reporting and Improve Decision-Making Support” You Ask ?

Most of these problems come down to data.

Whether you’ve got enterprise systems and custom analytics, or commencing the implementation of integrated reports, if your data is out of shape, you’re wasting your time and money.

The cost of what is a seemingly tiny issue – even if it’s duplicate customer records – is massive when you add the amount of time spent either re-working reports, working around, or deciding on what record to work with across each person that uses a customer record.

Step 1: Assess Master Data Health:

Most businesses have at least two systems that manage records of the same individual or company as they move through the sales and marketing process. Even with live integration, it’s common to have duplicates, gaps and discrepancies between two or more records regarding your customer or prospects if master data hasn’t been cleaned in some time.

Master data problems creep in over time – especially as a business grows and more systems are used, or more people are involved in data entry. The issues become noticeable in many ways. Examples include:

  • Accounts send multiple invoices for one billing cycle to clients by accident
  • Business Development Representatives or Account Executives have to click through multiple versions of the same client record to check which one should be updated
  • Mailing lists contain duplicate client records, so clients receive multiple of the same email from the business
  • Accounts don’t know to invoice a newly converted client
  • Pipeline reports or sales metrics are incorrect due to multiple records

What to do is: Assess the issue, fix what’s broken and present a framework that reduces the likelihood of master data issues in the future.

To get started, we’d run queries across your databases to assess the health of your master data. According to the number of gaps, duplicates or invalid records, we can assess the scale of the clean-up project and the best way to address it.

Step 2: Remedy The Issues

Validate Records. We design and apply rules to assist with massive validation of records so that batches of updates can be made automatically, and so that no critical data is lost.

Some batches – like those duplicate records that each have invoices attached, for instance, would have to be parked and merged or deactivated in a more manual fashion.

Step 3: Optimize Future Data Management

When working on a project, we aim to make data entry as fool-proof as possible. This is achieved in a number of ways, including:

  • Standardisation of data: It’s essential to standardize data rules and hierarchies or structures across your various systems. An example may be to produce an ‘Industry’ drop-down field rather than leaving a text area that’s up for interpretation. Mandatory fields with a shortlist of options that are easy to update will improve data accuracy down the road, and consistency among records.
  • Systems Integration: If integration isn’t an options between two systems like your CRM and Accounting module or ERP, you can have custom integration work completed.
  • Quality Checks: What I’ve done in the past to avoid issues is to build a dashboard – for instance, a Customer Dashboard – that provides a visual into how many records need attention to be considered complete, or ‘green-lighted’. You can also set up automated email alerts when a new Client Record has been generated in one system so an Administrator of any connected database can import the record or update their system to have a corresponding record.
  • Use Fit-For-Purpose Tools: Stop using Excel for reporting or analytics as much as possible. And try to get your teams thinking about reporting for performance improvement, not reporting for reporting’s sake. Many times, data health is a cultural issue; some organizations just allow for sloppy data which only slow the business down, muddle decision-making and reporting quality. Consider custom analytics that can present you with accurate, beautifully visual and easy to understand monthly reports at the click of a mouse.

This preliminary master data work will get you started on maturing your business information and decision-making support according to best-practice. It’s something you can provide to your IT team or outsource it to an operation like Blueprint Intelligence. I’ve personally performed this work for a series of organizations- I’m going to share these case studies with you in an upcoming blog.

In my next blog I’m going to share a case study where we performed this very process to achieve significant performance improvements, and valuable insights. My favourite moment is unveiling the analytic to see the faces of the management team. Almost every time the analytic presents a surprise to the business.

Stay tuned, or reach out to discuss your analytics needs.

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