Data is a main driver behind business strategy and projection, yet inaccurate data leads to poor or ineffectual decision making. As a result, bad data is costly. According to research conducted by IBM, bad data costs US businesses $3.1 trillion per year.
So it’s vitally important to use high-quality, accurate data for reliable insights that can positively impact your marketing, sales, and bottom line.
What type of data you collect, how you collect it and how you process it will all affect the quality of your insights. Find out the advantages and disadvantages of different data sources and discover the ground breaking data insight solution that draws meaningful, quality insights from your data in minutes.
Advantages and Disadvantages of Different Data Sources
- You can be specific about the kind of information you want to collect.
- Surveys can be conducted via email, online, over the phone or even in-person to reach customers with different preferences.
- You can easily segment participants into subgroups to better understand response differences.
- Participants may need an incentive to take part.
- Incentivisation can lead to bias.
- Survey fatigue (when participants get bored at a midpoint of the survey) can also lead to bias.
- Since open ended questioned are often difficult to analyse, survey designers tend to use closed-ended or questions which can be leading.
Review sites are a great way of retrieving honest insights directly from your existing customers. As well as general sites such as Google and Yelp, there are also dozens of industry-specific review sites such as TripAdvisor, OpenTable and Capterra.
- Reviews are organically collected and as such, they are more likely to be a true and honest reflection of the author’s feelings and opinions.
- They are freely and (in many cases) widely available.
Qualitative data is rich in insights.
- People only generally write reviews when they feel extremely strongly (positively or negatively) about the brand, product or service.
- Qualitative data takes a long time to harvest and organise.
CRM data is captured through website forms (e.g. sign up forms) and web analytics and is often populated with data from other sources mentioned in this article (namely social media and surveys). Information is aggregated to create a holistic profile of each customer.
- As with survey data, you can be specific about the kind of information you want. You can choose which fields to include to build a three-dimensional picture of your customers.
- You can track the customers’ interaction with your business e.g. purchase transactions, customer service interactions, time spent on website, etc.
- It captures your entire customer base.
- Aside from basic information (name and email address) asking for more information upon sign up can feel intrusive.
- To reduce barriers to entry on sign up, many choose to make fields optional, which means that datasets are often incomplete.
- People can be incentivised (e.g. with a discount code) to participate or complete all fields, which may lead you to bias.
Social Media Data
Social media data is gathered from social networks showing how users engage with your content. When most people talk about social media data they refer to quantitative statistics (the number of likes, shares, comments etc) but it is also rich in qualitative data which can be mined for more meaningful insights.
- Organically collected, these expose the real and true opinions and feelings of your customers.
- As well as conversation directed towards your brand, it also captures conversations made “behind your back.” What are your customers saying about you when you’re not in the room?
- Data is freely and widely available.
- Given the ubiquity of social media, in most instances, it captures a wide proportion of your consumer base.
- Qualitative data is rich in insights.
- Data is constantly generated meaning you can keep your finger on the pulse of your customer base.
- Difficult to capture and organise.
- Quantitative metrics lack consistency across networks and are therefore difficult to aggregate. For example, is a Facebook like equivalent to a Twitter retweet or a favourite?
- Quantitative metrics can be misleading or confusing. For example, a charity organisation may receive “sad” or “angry” reactions on Facebook which most social listening tools will register as a negative sentiment.
- Rapid turnover makes it difficult to update and track.
Enhance Data Insights with Solutions by Symanto
Symanto has developed solutions to counter many of the disadvantages of the different data sources mentioned above to improve the quality of your insights.
Use any and all data sources
The Symanto Insights Platform is a data insights solution that draws clear and meaningful insights from qualitative data wherever it’s captured.
- Surveys – Symanto has direct integration with SurveyMonkey and TypeForm
- Review sites & social media data – The Symanto Insights Platform is connected with over 75 review sites and online portals.
- CRM data – Upload your own data set from your CRM and choose which column you’d like Symanto to analyse.
This allows you to make the most of all relevant data sources at your disposal.
Get insights within minutes
Symanto automatically organises and analyses vast quantities of qualitative data within a matter of minutes. Our AI technology automates a process that would take months to manually organise, meaning you can repeat the process regularly to stay up to date on what people are saying about your brand online.
Rich insights on a general and granular level
Symanto’s Deep Learning AI technology scans conversations for brand sentiment, topic sentiment, emotion, and the psychographic traits of your consumers.
Get an overview of how your brand, product or service is performing. Find out how your brand is perceived in general and per topic, discover customer pain points, find out what motivates your customers to make a purchase from you.
The information is organised so that you can deep dive into the data so that you can easily navigate and explore the insights right down to reading comments to give insights their full context.
Deep Learning improves accuracy
Our AI technology is constantly improving its accuracy. Symanto’s text sentiment analysis is able to read a sentence in context before assigning a positive or negative sentence.
Consider the following comment: “Their tacos never fail to impress me.” A less advanced sentiment analysis tool may isolate the words “never” and “fail” and assign a negative sentiment. Symanto, on the other hand, identifies that the overall meaning of the sentence is positive.
Get In Touch
If your business is in need of a data insights solution to help you make decisions on marketing, product development & innovation, customer experience, brand health and even employee satisfaction, get in touch or book a free, personalised demonstration of the Symanto Insights Platform.