With the exponential utilization of technologies that capture data (the Internet of Things, social media, web cookies, etc.), data management has become a major priority for businesses regardless of their size.
Indeed, companies collect, store and analyze large volumes of customer data daily. They have the possibility as well to purchase databases or sell theirs to third parties. In general, customer data can be acquired by:
First, data helps you learn more about your customers / your audience: You can learn what exactly is luring your customers in and why they are choosing the product. Based on this, you can improve their customer experience. For instance, A/B testing works well to evaluate which call to action, visual, offer, etc. has the best impact for your customers.
Data management is useful to discern trends in their behaviours as well. Furthermore, this knowledge will support to segment your audience into several customer groups. From there, you can target each group through refined digital marketing strategies adapted to their behaviour. This way, you can reduce inefficiencies and maybe unveil potential sources of revenue.
In addition, segmentation is helpful to narrow down the optimal price range, according to the price tolerance, behaviour and demand of each group. Combined with past transactions and market research, you will have the necessary information to determine ideal pricing to maximize sales without lowering your margins or customer perception.
Moreover, data collected can give you valuable feedback to enhance your product or service quality in order to better meet your customers’ needs.
Overall, data gives you insights facilitating and supporting business decisions.
Additionally, for some businesses, data is a mean to secure more sensitive data: particularly in the banking industry, voice, facial or fingerprint recognition serve to authorize a user’s to access their financial information (that enables them to lower fraud risk).
It is easy to comprehend what all the rage is about but before being insights, customer data is raw data that needs to be sorted, structured and analyzed. Think of it as the difference between petrol and fuel. Your vehicle can only put into service the later to move forward. Raw data can add up to a large daily volume that no human could read fast enough to impact a business. According to Lucidworks (search technology), most companies only analyze around 10 % of the data collected. The unknown and unexploited data is known as dark data:
“The information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes (for example, analytics, business relationships and direct monetizing).” (Source: Gartner)
Dark data includes data that companies captured but are unsure how to exploit, but also data they are unsure or unaware they actually collected.
As stated before, the amount of data to go through is large and collected daily, so it is humanly extremely difficult to sort and analyze quickly enough. Thankfully, we have machines and computers in particular that operate even during non-business hours (and do not take smoking breaks J).
Going further than statistical models, data analysis methods like machine learning or deep learning (and artificial intelligence in general) are powerful allies to break down the large volume of data into actionable insight. Some artificial intelligence programs go as far as offering recommendations.
Navigating through all the collected data may be overwhelming at first, but luckily, there are some ready-made tools that you can operate:
A business intelligence (BI) software is designed to analyze via automated processes the exponential volume of business data in order to provide a better understanding of an organization’s strengths and weaknesses. They can include reporting, dashboards, online analytics processing, real-time analysis, cloud BI, data mining and predictive analytics, etc.
Mostly, all BI software are data visualization tools. They present data in a way that is easy to understand and use for decision-makers. Humans are visually driven by nature. Data visualization tools enable them to get real-time business-critical information, in an overview. Visualization (either with widgets, KPIs, charts, tables, or more commonly a mix of these) present information in defined spaces with different shape, colour and size to provide context and meaning. In a glance, thanks to BI technology, the decision-maker can identify trends and insights.
Data visualization is ideal to persuade as well. A chart or graph has a higher level of impact than simply displaying a table.
A Customer Relationship Management (CRM) tool is designed to enable businesses to establish long-term relationships with prospects and customers via personalized, meaningful interactions. The idea is that a business’ success is related to the relationship it builds with its customers.
CRM tools track customer interactions (and their history with the business) and service issues, store contact information and manage marketing campaigns. All that data is visible and accessible in one platform.
Some of the main business benefits of CRM are enhancing customer retention and customer satisfaction, boost sales and conversion rate, reduce lead costs. Furthermore, according to RingLead, 74% of CRM software users believe the tool enhanced their access to customer data.
Indeed, CRM tools display on one-page key information regarding potential leads from various channels and interactions with the prospect/customer (through emails, calls, social media, website, etc.). In that way, and provided the CRM database is accurately updated, this kind of software will support enlightened business decision-making.
As mentioned earlier, data management has become a major priority for businesses. Because it has, and because consumers are wary of the amount of data collected about them by so many organizations, governments build frameworks of regulations.
These regulations define data protection principles you must comply with when processing personal (including customers’) data.
Here are a few that could be interesting to look into:
Does your business have a high ratio of dark data? Are you looking into optimizing data management in your organization? Or simply stay compliant to the regulation? Our experts at Digital Plant could provide some guidance: contact us here.