If you keep your eyes on the road, you should know by now that with the so tech-driven and fast-paced world we live in, being data-driven can play a very important role in the way your new company evolves. Besides, it helps you predict market trends and customer’s (or potential ones!) behaviors! Thus, it provides you useful insights on what and when to invest to increase your productivity and achieve better results. So let’s focus in data analysis for today and how Salesforce can help you.
With your company still in the first stages of operations, you are probably working hard to make the best use of your data. You’re using several data collection techniques, and running reports. However, you have not yet achieved the so promised results. Fear nothing, we are here to help you!
We’ve put together a series of potential mistakes new companies make when they go for a more data-driven approach. Check them out to see whether you had fallen into a trap.
Here’s our table of contents for today:
1. Common Pitfalls
Above, find a list of all the common pitfalls you may find when making your data analysis:
Make use of funding to invest in a business intelligence tool
Data analysis requires industry and business knowledge that even the best BI tool can’t get you by itself. In such a short period of time, it’s possible that neither you nor your team acquired the necessary skills to interpret this information. And, more important than collecting and receiving data, is to know how to analyze it, understand long-term trends, and learn to ask the right questions, something that only comes with experience. Once you gain this sensibility, you are ready to make the best use of a data analysis tool!
Focus on metrics instead of goals
You might be all over the place, trying to gather data about absolutely everything, instead of focusing on how you want to place your company in the long-term. Without clear goals established, it is hard to understand what to measure and how. For instance, you might be looking at how well your products are behaving rather than setting targets.
A great effort in offer personalization
Startups tend to bet heavily on product and service customization early on. This is costly both in terms of money and time, especially when you are new to the market, and may not positively reflect on the company. After all, it takes time to know your customers and to understand what and how personalisation works.
Neglecting Outliers
Another common mistake startups tend to make is not paying enough attention to slight (sometimes relevant) downfalls. If the results are generally good or at least reasonable, managers think these drops are normal. But they can be often related to some flaws in business processes, problems with the website, etc. At an early stage, everything should be analyzed and interpreted.
Knowledge stored into one single person and non-existent processes
Knowledge is often centered in one or two people inside small organizations. In startup companies members tend to rely greatly upon the founder to make decisions. However, it is fundamental to share this knowledge and communicate customer requirements and quirks. That way, everyone can work effectively with them and extract insightful information about Offers, personalization, discounts, find points to improve in the future, etc.
Unstructured/Disorganized Data
Lack of processes can lead to unstructured or disorganized data, contributing to the loss of information and poor communication between teams and the client – and no client deserves to be addressed by someone who never provides the answers required, at least in a timely manner. Take a little step back and try to analyze how do you currently receive insightful information – is the data difficult to analyze? Can you reach out to any conclusions from that data? Do you equally treat the data received from your sources?
Whether you are using qualitative surveys, social media, or audio calls to extract, you might be missing small details that come from old purchases, renewal patterns, and customer feedback, helpful to make predictions and to be on the lookout for new trends.
It could also be the case you have your data pretty well structured. But you are also working it in different places, with each team using their preferred tool. While collecting and analysing information in a decentralized way, you might not be properly following up on leads or responding to your customers in a timely manner, looking for knowledge that someone in your company already has.
Not paying enough attention to market and competitors
With so much focus on analyzing data coming from your customer’s behaviors, customer feedback, sales trends, etc., absorbed in the “hype” of launching a new company, you could not be paying due attention to the market and competitors.
One must remember that is a very fast-paced era, with every company trying to renew themselves, so any slip can give a competitive advantage to your competitors. It is important to always be aware and try to anticipate changes that could leave your company behind.
If any of these points are familiar to you, it’s likely that you are using your data properly. You’re making data-supported business decisions, or clearly understanding your customers’ needs. This can obviously lead to poor customization, to loss of competitive advantage, and to an increase in the number of wasted opportunities.
2. Tips to avoid making bad use of data
Use this easy tips to simply avoid making bad use of the data you’re storing:
1. Establish smart goals
Start by establishing smart goals. Establish then the actions to achieve your goals and collect the metrics. Then, you can think of expanding the set of metrics used.
2. Learn to ask good questions
This only comes with experience and market/industry knowledge. Once you know what to ask, how the market is performing, how can you analyze trends, you can then focus on setting up a business intelligence tool that will help you support your decisions.
3. Data Centralization
Work your data in a centralized place and establish common rules to be followed by all your team members, such as naming conventions and processes to combine data from different sources in a comparable way, to be followed by all your team members. In this way, you make sure everyone has the same and more correct understanding of inbound information and has access to it when needed.
4. Invest in a CRM System
A CRM system will help you to maintain your data centralized and clean. It avoids data duplication, and makes it easier to find and insert information. Your coworkers will no longer need to lose time searching for customer information. Or even troubleshooting issues their colleagues already know the answers. Instead, they could focus on their productivity and closing deals.
3. How can Salesforce help you on data analysis?
Find below how Salesforce will help you in your process of data analysis:
- It’s a very powerful CRM system. It allows companies to have all the information about potential leads, customers, communications, call recordings, opportunities, forecasting, and market trends in one single place.
- Teams and departments can collaboratively work together and collect the best insights with just a click away.
- Adjust access to data and other permissions. You can then make sure that only certain co-workers are able to edit and insert information, making it more reliable.
- Possibility to customize page layouts according to each team/department’s needs. Also provide them with an easier navigation experience and making them find the information they need in a faster way.
- Automate processes and notifications so that you are always aware of what is going on and reduce manual work. Try automation instead of trying to keep the data in the system clean and trustworthy.
I hope this article is helpful for your company’s data-driven journey. If you find any question, feel free to ask us anything. Also, don’t forget to subscribe our Knowledge Center.
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