Getting business insights from data by combining software analytics. How Synder Insights can help companies grow.<\/p>\n\n\n\n\n\n\n\n\n
Having data is a bit like having food ingredients, they can remain untouched and unutilized (hello, the bottom drawer of the fridge) or they can be turned into a gourmet meal. Same ingredients, but different outcomes. The good thing about data is that you don\u2019t need to be a master chef to get amazing things from it. It doesn\u2019t spoil, so you can even draw on historical data to get insights. And your data is always there, waiting to be used and analyzed. So let\u2019s see how we can take advantage of it to help your business grow.<\/p>\n\n\n\n
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1. How Data Is Turned Into Business Insights<\/a><\/p>\n\t 2. Do We Need People to Evaluate the Insights?<\/a><\/p>\n\t 3. How Synder Insights Can Make Companies Grow<\/a><\/p>\n\n\n\n <\/p>\n\n\n\n The journey that data takes from its raw and unstructured form to the actionable insights – that\u2019s what drives the decision-making and becomes a part of a bigger world of business intelligence (BI). And the vehicle that takes you there is the right intuitive software like Synder Insights<\/a>. <\/p>\n\n\n\n Every company collects data, in abundance actually, but not every type of information can be used to make inferences. On the one hand, data collection can be happening simply as a byproduct of operations you already perform, like invoicing for example. On the other hand, it can be created specifically to acquire new types of data. Quite a lot of marketing strategies are based on the latter model.<\/p>\n\n\n\n Once the data is collected in its unstructured form, it needs to be arranged in such a way that it can be fed into the analytical software (though some rare software can also mine unstructured data). That can sometimes be a cumbersome task, as some data collection spreadsheets might not be compatible with the software you use. Or perhaps, it\u2019s only working with the data from some of your channels but not all, making it impossible for you to draw conclusions about your whole business, – all platforms included. <\/p>\n\n\n\n That\u2019s why having an integration like Synder is a good choice – not only does it pull data from all of your channels, but also takes away the step of data structuring by using financials from your day-to-today bookkeeping. <\/p>\n\n\n\n Once your data is arranged, it\u2019s ready to be analyzed. Good software is your best friend here, as with its help you can discover nuggets hidden in your data and understand your business better. Analytics usually starts with asking questions, for example: \u2018What\u2019s my <\/em>Customer Lifetime Value (CLV)<\/em><\/a>?\u2019<\/em> but it can also take the form of exploration. A lot of great ideas and discoveries were stumbled upon by chance, so don\u2019t dismiss this opportunity – you never know what you may find. One sure thing, you’ll get a much fuller understanding of your business. <\/p>\n\n\n\n While complex and extended analytics is great for quarterly or yearly reports, on a daily basis, having a concise report of your business\u2019s vitals is more valuable, both in terms of money and efficiency. What you want is to touch base with how your company is performing and keep the proverbial hand on the pulse. <\/p>\n\n\n\n While analytics is a process, insight is the meaning behind the result of the analysis. Having a clear understanding of what the output means and how it can be used to improve the business is the key. <\/p>\n\n\n\n Some analytical software is nondirective, meaning they allow you to perform the analysis of the data the way you see fit. In other words, you\u2019re the driver of what happens during the process, including what questions and insights you want to explore. This approach is suitable for those who are very well-versed in data analysis and exploration. <\/p>\n\n\n\n Other types of software, like Synder Insights, are more directive and come with a pre-made set of questions that they\u2019re trying to answer, just like a doctor’s check-up. Here the insights are already generated based on your data, and you get access to a set of reports, like your \u2018top performing product\u2019 or \u2018top refunded product\u2019. <\/p>\n\n\n\n Data insights are a part of business intelligence (BI), a larger concept that encompasses all data-driven technologies and strategies that companies use. BI creates a web of accurate data-based insights that can function as a central brain of an organization – you just have to know how to use it.<\/p>\n\n\n\n With the rapid development of new technologies, BI is one of the top-growing business fields. That\u2019s why building a network of BI technologies is a cutting-edge solution for business owners nowadays. <\/p>\n\n\n\n It might seem that all the work is done by software, and while that\u2019s true for the most part, a good and careful look at the results of data analysis and the data itself will help in getting the right conclusions. Let\u2019s investigate the most common concepts to look out for when dealing with business insights. <\/p>\n\n\n\n A confounding variable is a variable that you haven\u2019t accounted for that is causing you to assume a relationship between the two other variables you measure. Let\u2019s look at an example. You\u2019re setting up a new marketing strategy in a country that hasn\u2019t previously been profitable for your business, but you\u2019ve recently noticed a significant jump in sales in this region. Of course, the first conclusion is that your new strategy is working, but it\u2019s prudent to check whether it can be explained otherwise. And just by checking the latest news in that country, you\u2019ve realized that a big national festivity was being celebrated and your products were the ones sought after. This new information shows that you can\u2019t be sure whether the spike in sales was caused by your new marketing strategy, higher demand due to celebrations, or a mix of both. <\/p>\n\n\n\n Being the devil\u2019s advocate is probably not the most attractive position within a company, as the role literally means poking at things and finding holes, but it\u2019s invaluable in keeping the business in check. So whenever you see that there\u2019s more to the problem – don\u2019t hesitate to speak up. <\/p>\n\n\n\n It\u2019s recommended to visualize your data, because some information may get lost once it\u2019s pulled into numbers. Coming back to the example above, if you saw a histogram of all products sold in the new market during the last month, you could probably see that only a specific group of items rose in sales, rather than your sales across most items. This uneven distribution could point to a higher demand for products, rather than your new marketing efforts. <\/p>\n\n\n\n Sometimes, what looks like outliers on a plot, might turn out to be a unique cohort of customers, which you didn\u2019t know existed and whose needs you can better meet now. <\/p>\n\n\n\n Does your concept measure what it is supposed to measure? That\u2019s a very tricky question. If applied correctly, financial measures are mostly valid for their purpose, but some marketing strategies should be mindful of validity. <\/p>\n\n\n\n Creating a survey<\/a>, or even a single question asking your customers about their experience with your product, has to be carefully thought out to ensure you measure what you\u2019re after. When checking customer satisfaction, a simple question: \u2018How useful do you find the product?\u2019<\/em>, doesn\u2019t fully capture the concept of satisfaction and overlaps with the product parameters. A customer might be very satisfied with a product but not see it through the lens of usefulness – buying a poster with their favorite superhero could be a good example here.<\/p>\n\n\n\n That\u2019s why it\u2019s best to check if the questions you create really are measuring what they\u2019re intended to so that you can get accurate insights.<\/p>\n\n\n\n This famous line is Statistics 101 and something to always keep in mind. When we switch on the news, we usually see correlations being shown as causal events, so this misconception is unfortunately quite common. Correlation refers to the strength of the linear relationship between the two variables. Causation is all about how one variable affects<\/em> the other.<\/p>\n\n\n\n There\u2019s a positive correlation between wearing sandals and eating ice cream, which means that as the number of people wearing sandals increases, the number of people eating ice cream also increases. But surmising that wearing sandals causes<\/em> people to eat more ice cream is inaccurate – we all know it\u2019s all due to the hot weather, right? <\/p>\n\n\n\n With more complex examples within the business sphere, it can sometimes be difficult to distinguish whether the report describes correlation or causation. Pouring efforts into correlation is a money pit, as no amount spent will have any effect on the other variable, since there\u2019s no causal effect.<\/p>\n\n\n\n Hence, in business, it\u2019s A\/B testing that\u2019s most commonly used to test hypotheses to find causality. And indeed, a well-designed experiment can give you solid data to draw conclusions from. <\/p>\n\n\n\n Synder Insights can become your all-in-one source of truth for strategic decision-making. It pulls real-time data, giving you an instant, accurate, and up-to-date report on your business\u2019s vitals. The reports span financial metrics as well as product and customer-related insights. We\u2019ll look at some of them more closely. <\/p>\n\n\n\n There are several reports in the Synder Insights dashboard where you can obtain information about your products. Below you\u2019ll find only a few reports that are available through the analytics platform, head here<\/a> for more features. <\/p>\n\n\n\n Synder Insights lists all of the top-performing products in terms of gross income, but the report can also be sorted by the amounts earned, items sold, and other categories. This feature lets you see what your hot sellers are, and also gives direction as to which of the products would benefit from more marketing. The items can be arranged based on the regions you operate in and the platforms you use, so you can see how they compare and where most of your revenue comes from.<\/p>\n\n\n\n On the opposite spectrum lies another interesting feature: top refunded product<\/a>. Even though we hope that we sell the best quality items, refunds are part of our life and we need to learn to deal with them as quickly as possible. Sometimes there might be an inherent problem with the product or just a mistake in packaging – each case requires a different solution. Seeing these problems in real time lets you spot those situations and nip them in the bud.<\/p>\n\n\n\n The products most purchased together<\/a> report gives insight into customers\u2019 behavior and preferences. By knowing which products are being sold together organically, you can better cater to your customers\u2019 needs. Grouping these products will further increase your sales as it provides your customers with the exact things they\u2019re looking for. <\/p>\n\n\n\n Whether it\u2019s a product or service that\u2019s being offered, these are the customers and users that are at the heart of any business. Let\u2019s see how Synder Insights helps you hear their voices.<\/p>\n\n\n\n Purchase frequency<\/a> is one of the indicators of customer loyalty. If the same customers keep buying products from you and returning to your shop, it means that customer loyalty is high. It also lets you have a sneak peek into the conversion of your marketing strategies. With increased efforts in marketing, there should be a significant jump in purchase frequency – your customers will keep coming back to your store for more.<\/p>\n\n\n\nHow Data Is Turned Into Business Insights<\/strong><\/span><\/h2>\n\n\n\n
Data collection and structuring<\/h3>\n\n\n\n
Analytics and the right software<\/h3>\n\n\n\n
How to find insights?<\/h3>\n\n\n\n
What is business intelligence (BI)?<\/h3>\n\n\n\n
Do We Need People to Evaluate the Insights?<\/strong><\/span><\/h2>\n\n\n\n
Check for a confounding variable <\/h3>\n\n\n\n
Graphing your data<\/h3>\n\n\n\n
Checking for validity<\/h3>\n\n\n\n
Correlation doesn\u2019t imply causation<\/h3>\n\n\n\n
How Synder Insights Can Make Companies Grow<\/strong><\/span><\/h2>\n\n\n\n
Insights about product performance<\/h3>\n\n\n\n
Top performing product<\/h4>\n\n\n\n
Top refunded product<\/h4>\n\n\n\n
Products most purchased together<\/h4>\n\n\n\n
Insights about customers and users<\/h3>\n\n\n\n
Purchase Frequency<\/h4>\n\n\n\n
New vs. returning customers<\/h4>\n\n\n\n