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7 steps to implement Analytics in your company

Updated: May 31, 2023

Learn about the main steps to implement Sales & Marketing Analytics in your company and find out what precautions are needed.

If you want to grow and scale your sales, you certainly need to implement Sales & Marketing Analytics in your company, or simply Analytics.


Before investing in marketing, it is necessary to take the time to analyze customer profiles, the information they consume and share on a daily basis, market news and even the actions of competitors.


It is based on data like these that companies develop strategies to strengthen their brand, increase visibility and improve their customer base, for example.


If you still don't know the basic concepts for such a strategy, also read “Marketing Analytics: What is it and why is it important”.


Analytics is closely related to the Big Data phenomenon. That is, an explosive growth of data in the digital environment. These days, we have infinite data at our disposal, since it is possible to track almost everything virtually.


Nor can we forget technologies such as BI - Business Intelligence, which are also indispensable resources for those who want to make better decisions.


Why should you implement Analytics in your company?


Analytics considers all data important to your business and creates a common relationship between them. By combining and linking data from diverse sources, it is possible to make more solid and accurate decisions within the company, in addition to executing programs more efficiently.


However, remember that for this strategy to work, it is necessary to adopt a data driven culture in your organization. That is, people, processes and systems attuned to the same objective of providing decisions and actions based on data and numbers.


7 steps to implement Analytics in your company:


We want to help you get your hands dirty. Let's go step by step to implement Analytics in your company with a focus on Sales & Marketing, that is, aiming at scale gains. follow up.


1. Understand what your company wants to measure

There are several aspects to a marketing campaign that you can measure: leads captured, conversion rates and brand awareness, among others. Understand the real problem you are trying to solve or the insight you are trying to capture when starting a data analysis.


2. Establish a reference

What's behind a successful campaign? Having a benchmark helps you determine the types of metrics and data marketers can collect. For example, if the company's goal is to increase brand awareness, the benchmark of success might be a higher percentage of brand loyalty in a customer panel, rather than an impression or click online.


3. Assess your company's capabilities

What is your company doing today? What are the weaknesses and strengths? Whether identifying the media most likely to convert or measuring campaign results, understanding a company's capabilities can help strengthen its strategies.


4. Look for optimization recommendations

Once insights are collected, the ability to present recommendations to improve underperforming ads and campaigns is crucial. For example, the data might show that a consumer engaged with branded content only in the afternoon, informing a change in strategy to run the campaign on the way to the consumer's home, rather than the morning route.


5. Understand your company's gift

Is the company communicating correctly with the public? What do they think and say about the company? Is it present on the correct digital channels where they are? Ask these questions within your company to better understand how it is performing in the market today.


6. Know how to influence the future

This is a very important step when performing data analysis. Is your company able to use the collected and analyzed history to influence and change the future of the organization?


When well analyzed, marketing campaigns can evolve more and more, making your decisions more successful.


7. Use Web Analytics Tools

There are many marketing tools that help a lot in optimizing processes. However, you can't just bet on these features and trust them to do all the rest of the work.


Only data-oriented professionals with good analytical skills will be able to collect the best data and understand how it can be applied to each type of strategy. However, with the help of some tools it is possible to direct this work even more. Check out some suggestions below:

  • Apache-Superset (Python)

  • Databox

  • Google Analytics

  • Google Data Studio

  • Improvado

  • Klipfolio

  • Microsoft PowerBI

  • Qlik Sense

  • Stract

  • Supermetrics

  • Tableau

  • Zoho Analytics

The choice of tool will depend on the objective of the strategy, which can be to analyze the behavior of consumers, competitors, engagement in social networks, assertiveness rates and campaign reach, sales, stock position, among other indicators.


6 mistakes you need to avoid when implementing analytics:


There are some common mistakes you should avoid when implementing Marketing Analytics in your company and below we bring you some of them.


1. Waste of Time

Excessive waste of time or excessive focus on the process is a very common mistake. This can happen for several reasons:

Lack of clear and well-aligned strategies between teams;

Excessive analysis done manually (reports and excel sheets);

Lack of professionals dedicated to the “Analytics Front” in the organization, which generates rework and timid advances.


2. Lack of documentation of the preliminary results obtained

There is no way to guarantee the performance of a strategy if there is no record of it. This includes performance data as well as objectives, targets and plans.


3. Monitoring the wrong metrics

Another very common mistake is monitoring metrics that are irrelevant to your business. It is necessary to aim at the metrics that really impact your business. These are the famous KPIs – Key Performance Indicators or Key Performance Indicators.


4. Summarize “Front Analytics” to the simple acquisition of tools

The use of tools is important to automate and make the process scalable. However, the solution lies more in human resources combined with technological tools.


5. Lack of Governance

Analytics requires governance and discipline. Dealing with thousands or millions of data and information from different sources and different periods requires an agile and meritocratic management model. Once again, the importance of qualified people guided by strategic plans is reinforced.


6. Ignore the Power of Data Visualization

Presenting the results of a campaign to business executives, for example, suggests positive impacts on discussion forums and strategic committees. But if the data is taken only as numbers and tables, it can frustrate expectations and not send the right message. Data well illustrated in reports and analytics applications summarize the importance of Data Viz on an Analytics front in any organization.


What we recommend you do after reading this article:

With the help of Sales & Marketing Analytics strategies and digital solutions, it is possible to achieve very good results, using data in favor of the organization and increasing the performance of actions and strategies. And this proves to be an excellent investment given the reasons we have listed in the lines above.


Falqon - with 10 years of experience, more than 200 projects and more than 2 thousand experts in Big Data & Analytics impacted by our solutions - defends the thesis that companies from any segment need to know their audience and study their behavior, purchase history , research carried out and others so that they design their products and create their strategies aiming at high performance.


If you have read this far, you have just taken the first step towards implementing an Analytics Front in your organization. As a second step, how about watching the presentation of a successful case with one of our clients in your sector?


Get in touch and find out how we can help you!


by Félix Muniz, CEO - Falqon Specialist in Strategy and Management for Technology Businesses; Startup Maker and Entrepreneur.

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