Better Data Enables Better Quality and Efficiency

The black box is the same concept as your cable box: the higher the quality of the box’s components, the better resolution you’ll see on TV.  In our analogy, the components in your sales black box are the bits of data you input; the higher quality data you put in to your sales black box, the higher the quality of the distribution network or audience you’ll see for your product. Quality data is crucial for selling any product to the right audience. If your data inputs are not flushed out and out-of-date, then your product is doomed to fail from the start. Lacking data quality will not only yield poor results, but it can jeopardize any future marketing or sales campaign.  For today’s blog post, we’ll help clarify how analytics yield better sales data, but also how better sales data can be used for segmentation, target market decisions, and targeting the right companies.

What are Analytics and Data

To start, analytics is the discovery, interpretation, and communication of meaningful patterns in data. In other words, analytics can take data, predict validity, and predict the success of certain applications. In our analogy, analytics is the Neilson Family inside our black box; if employees with X title yielded poor results, then your data lacks quality or you’re not targeting the best audience. Measuring the success of your product can help guide your sales team to marketing towards a target-rich audience, based on commonalities between the success group and an untargeted audience. However, there’s one danger in analytics: the quality of its results is only as strong as its data input. This is why it’s crucially important to have quality control over your data.

Steps to Better Data Quality

If you’ve noticed a lack in quality control over your data, then you may want to pay attention to the following steps.  With the aid of online tools and dedicated business development, we’ve maintained quality control with the following 6 easy steps:

  1. Profile your data – Just like with any research, you have to document where your data came from. Doing this will improve the reliability of trusted sources. Also, note the potential problems with your data: Is everything in the right category? How recently was the information updated? Etc.
  2. Control your data – Use automated tools, or keep a schedule of the amount of time each day needed to clean your data. Prioritize the data clean-up efforts: start with the highly visible info, like e-mails and titles, then fix business-specific info. It also helps to encourage all users to fix their data; if a contact’s number is invalid, then update it before moving on to the next.
  3. Integrate your data – If you use multiple systems, then see if there’s an automated solution where, when you update data in one program, the information syncs with all other data programs. This will keep everything consistent and prevent conflicting information. This function can be utilized and is popular in programs like
  4. Augment your data – If you have a third-party program, like Dun & Bradstreet or Hoover’s, then you can gather additional information to increase the quality of your data. To understand what data is valuable, survey your sales and marketing teams to see what they need most.
  5. Monitor your data – Once you obtain that quality data, make sure the information stays pristine. Ensure that all information is confirmed from multiple sources, if not the direct source itself, before you update it. Programs to utilize include Insideview,, LinkedIn, Jigsaw, etc.
  6. Commit to data quality control – Ensure that everyone follows your quality control process. Users need to know the importance of maintaining quality data within their campaigns.  Once initial training is over, don’t be afraid to give each rep their own responsibility in quality control; trust that your solution is effective and that your training is successful.

Lastly, having quality data will reassure that you know what your audience is. High quality data can guide you towards the most effective target marketing decisions, as well as your ideal target audience. To incorporate this into our preexisting theme of TV, it’s the equivalent to owning your own network and knowing your viewer fan-base. If you notice more viewers like the sitcoms you air, then you wouldn’t air a reality TV show when that audience is viewing your channel. Maintaining quality data will ensure that you know your audience, can easily find your ideal target audience, thus saving time and being more efficient with it. The same principle applies to targeting the right companies; you wouldn’t sell TVs to a car dealership, would you? So maintaining quality control on company information is just as important when targeting companies as a whole. Having quality control over your leads and companies can improve the segmentation of your data, thus accurately categorizing leads/companies. Once segmented accurately, you can find the ideal target audience for your product based on the appropriate criteria for your product.

If you are going to take any quality information from this article, then please let it be the significance of incorporating and maintaining quality control over your data. Having quality data yields more accurate analytics, thus narrowing down (or effectively widening) your target audience based on the product’s success. As we discussed, you can incorporate quality control starting with 6 easy steps, like profiling, controlling and monitoring your data, amongst others. Once you have a functioning quality control system, it’s important to maintain it whether it’s done by one person, or multiple. With quality information, you can feel more confident in finding and controlling the target-audience; incorporating leads, contacts, and companies based on measured success. Tying it back to our allegory, the analytics, quality control, and measured success are the components inside your black-box; with quality components, you’ll see the brightest and clearest picture.  The black-box of sales is an inseparable part of every salesperson, and controlling the data that goes into it ensures that the quality portion is maximized, creating a better black box.

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