How to Use Data Sets in Communications Efforts
The astonishing increase of available data—all the information that we are now generating and businesses can store—has increased the demand for data scientists and analytical experts.
We are awash in data, but it only has value if we know how to use it.
Communications professionals can look beyond the metrics they are collecting to measure communications activity, because the range of data collected by an organisation can help to inform and shape company communications efforts.
Customer service data
Most companies, whether they are B2B or B2C, collect data about customer interactions. This data can provide a great deal of insight into how communications to target audiences should be conducted.
After all, when a customer contacts a company, there is generally a reason for it—good or bad.
Let’s start with the good. If a customer takes time out of his or her day to contact a company with a compliment, you’re doing something right. Here are some ways that data can be used:
- A positive customer story could be used internally, boosting morale and showing how a company can really make a difference in someone’s life;
- It can be used externally, as a sales or marketing testimonial (check first if you plan on using a name);
- If it’s really impactful, the story could present a possible positive media opportunity. (Hospitals highlighting patients who have overcome incredible odds are a good example of this type of story.)
- For compliments that don’t quite reach the level of the above examples, when collected and studied in aggregate, can provide useful guideposts on what attributes are resonating with your audience. Use this information to refine messaging for future communications.
Now, on to the bad. Customers who share negative experiences are communicating pain points. A business can use this feedback to do everything from refine processes to changing a product, to implementing a full-out recall, depending on what factors are at play.
But how can communicators use this information? First, by simply paying attention to negative customer feedback, PR can potentially head off a crisis (again, this depends on the magnitude and severity of the complaints). On a lesser scale, it can determine how you position the brand when you speak to the media. If customers are confused or have questions about a product, you can use this information to develop content for your owned properties, such as crafting a blog post that answers questions, or revamp the FAQ section of a website.
View your customer service feedback as a direct view into the minds of your audience, and use that insight to craft communications.
Logistical information might seem like an off-target data set for communicators, but that’s only if one is viewing communications through a very narrow lens. Consider the customer service data discussed above. Logistical data is all of the information collected on the processes that facilitate the delivery of goods and services to customers, end to end. If logistical data is relevant to customers, and customer service data is relevant to communications, then logistical data also is relevant to communications.
Logistical data can reveal potential warning signs that would be useful in determining the timing and messaging if customer and client expectations might be missed. It can also be conveyed to customer service representatives so that they are appropriately informed when customer questions arise.
For instance, you recently made a purchase at a store you frequently shop at and mailed a return for a piece of clothing. However, you noticed an extended delay in the posting of the return credit which was taking much longer than you have previously experienced. So you call the company up and the customer service representative informed you that due to the recent store-wide promotion they were running, there was a high return volume and there were merchandise that were returned but yet to be processed.
This back-of the house logistical information, provided to the customer-facing representative, enabled that representative to manage customer expectations and it also showed that the company had strong internal communications for all team members on its internal processes.
This is where the real treasure trove of information is—not just for businesses, but for municipal governments too. It’s a bit of a misnomer to suggest that we are just now beginning to collect data. Most companies and governmental entities have been collecting data for years, but it’s often sitting unused in a variety of formats: paper files in boxes, floppy discs, spreadsheets that reside on individual hard drives, or data from old software programs that are now defunct.
The greatest challenge with this information is getting it into a useable format. That process alone can be daunting—and expensive, depending on how much information there is and how troublesome it is to wrangle into a standard format.
For organisations with tight budgets—this includes local governments who are stewards of taxpayer dollars—the debate between the upfront spending to standardise the data versus the money that will be saved once the data can show where probable efficiencies are has been a formidable stumbling block.
Now, with abundant case studies showing benefits, businesses can find examples of success stories that they can relate to, and the spend doesn’t seem so risky.
Think about pairing historical local weather data with a retail store’s staffing numbers, store traffic, and sales figures for a decade. You’d be able to gain visibility into how things like snowstorms affect a store’s foot traffic and be better able to schedule the right number of salespeople. You can drill down even more: what are they buying? Analysis of Big Data is how Walmart learned back in 2004 that in addition to bottled water, flashlights, and batteries, people stocked up on strawberry Pop-Tarts. They use that data to plan distribution (note again, the logistical data mentioned above) and make sure stores are stocked in the days leading up to a possible hurricane landfall.
These improved business outcomes also improve communications. With historical patterns and understanding what the data can predict, crafting the right statements, posting the right information pieces on websites, and even sharing the right content on social channels becomes easier and more efficient.
Communicators can use data directly or indirectly to improve who they communicate with, the messages they use in that communication, and how they can determine the best channels to convey their messages.