By Fernando Berrocal

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From the outside, building a business startup could seem a simple process to you as a prospective and very well-informed future startup entrepreneur. However, this is never an easy path to take in any circumstance. You might anticipate that your startup's customer base will grow as a result of your efforts to make it expand. There, you'll start to provide new products to your customer base, and you'll need to hire more people to accomplish these goals.

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Nevertheless, what the outside world doesn't see is the excessive amount of data for which you end up being accountable. Today`s handling of data, even for the most basic type of startup, can be obtained in a very high quantity of different data. This specific startup scenario didn`t exist just a decade ago. All of this data must be gathered, handled, and protected following the most recent privacy regulations available.

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According to Validity’s State of CRM Data Management 2022 reseach, data is the lifeblood of their businesses worldwide and a major growth driver.  So, what’s the flip side of this?  44% of respondents have said that bad Customer Relationship Management (CRM) data caused their business to lose more than 10% of its yearly revenue. Startups cannot afford this during times of rapid expansion, especially in the present unstable economy. In the present startup blog article, we will go over the data problems that small businesses must overcome today and the best methods for managing and safeguarding large amounts of data.

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The SMB Data Environment

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Startup businesses operate at a lightning-fast speed that is perpetually evolving. There is little time to identify the data you need to collect. Also, your reasons for collecting and maintaining data exist since startup executives have so many priorities to address. For simplicity's sake, you might begin with a very basic CRM system in the early phases of your business’ growth.

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However, these systems can easily grow burdensome and even hurt your startup. Aspects are added to the CRM with little to no governance each time a new data piece needs to be gathered. The same data may end up being gathered inconsistently and in different locations as a result.

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Data inconsistency and probable income loss result if we magnify that over hundreds of data points across thousands of records. Around 75% of respondents to Validity's poll claimed that duplication and/or insufficient outreach motivated by bad data quality results in the loss of clients. If the practice of gathering the same data in many locations is not broken early on, it could spiral out of control and need significant investment in future data reconciliation operations.

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Privacy is Intentional

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There is an increased demand on Small and Medium Businesses (SMBs) and Fortune 500 businesses to emphasize customer privacy and the ethical acquisition of user data as privacy rules like GDPR and the prospective American Data Privacy and Protection Act keep popping up.  According to 25% of survey participants, their organization's leadership is aware of data quality challenges but does not support any specific data quality measures. This is particularly concerning in terms of privacy compliance because businesses risk substantial fines and future legal problems if best practices aren't put in place right away to encourage the ethical collection and safeguarding of data.

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For products to succeed, the mindset of privacy by design must be taken into consideration. Startup executives should establish privacy and security safeguards early on and make sure that all divisions and personnel are aware of and compliant with them. This will shield your business from potentially breaking privacy laws and prevent costly efforts to retroactively adopt restrictions in the future.

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Implementing Data Productivity 

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Startups can get off to the right start by putting data productivity first. Data productivity is the rise in team output that results from making data simple to enter, locate, and update no matter its source. You can make CRM data more accessible and simpler to input by eliminating friction from any process where employees, especially in sales and services, engage with it. Your teams' accuracy, output, and efficiency consequently increase, directly affecting your bottom line: 96% of respondents claimed that proper CRM data increase their business' conversion rates.

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Instead of admins and team leaders trying to retrofit productivity solutions after issues occur, putting processes in place early in your organization's growth assures that those processes scale. Start by identifying obstacles to updating your data to become more productive with data. Which teams are in charge of updating the data? What particular data are they in charge of? What is the current procedure for updating team members' data? 

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Once you've identified these problems, come up with a strategy to address each one–such as making your CRM easier to use, or automating the procedures needed to update it. Set expectations, get user input, and give the appropriate training right away when you're establishing new data management processes, like using a CRM, to make sure you can repeat similar procedures in the future.

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Data Partnerships

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As businesses expand, they'll inevitably want to forge alliances that expose their products to new markets and create new revenue streams. But one factor that's frequently disregarded is the data flow between partner platforms. An organization that processes or stores customer data must have a complete understanding of the effects that every technology it implements will have on that data. Startups need to use privacy policies, a data processing agreement, and a list of sub-processors to keep their customers, prospects, and partners informed about their security and privacy practices. The sooner these practices are adopted, the more you can build confidence and improve interactions with suppliers, partners, and clients.

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Optimal Practices for Data–At Scale

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Data best practices must serve as the cornerstone of your startup as it develops. You can reduce risk and reproduce success as you scale by building a solid foundation of privacy by design, data productivity, and intelligent data relationships. The main line: as you scale, data best practices shouldn't alter. Instead, who is in charge of these processes, and how they are managed, controlled, and carried out will change. 

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For instance, a business in its early stages can rely on controls or templates offered by the platform they're employing. Later, when the startup grows, a Privacy and Security team headed by a Chief Information Security Officer (CISO) will form, and it will be their job to ensure compliance. Eighty-four percent of poll participants claimed they use data to stand out from the competition. Your company will be prepared for success on any scale if you can demonstrate that it understands data controls and best practices and is working to put them into practice.

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