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Snowflake believes companies will gain from the implementation of AI and ML in their marketing strategies: Vimal Venkatram

by Kalpana Ravi
June 15, 2021
in Exclusive, Featured
Reading Time: 7 mins read
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Snowflake believes companies will gain from the implementation of AI and ML in their marketing strategies: Vimal Venkatram, Snowflake India
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Snowflake Inc. is a cloud-based data-warehousing company that was founded in 2012. It has raised more than $1.4 billion in venture capital and is based in San Mateo, California. Snowflake offers a cloud-based data storage and analytics service, generally termed “data warehouse-as-a-service”. It allows corporate users to store and analyze data using cloud-based hardware and software.

Snowflake started its India story in May 2020. MediaNews4U spoke to Vimal Venkatram – Country Manager – Snowflake India, on their India operations, the importance of Data Analytics, the use of Artificial Intelligence (AI) & Machine Learning (ML) to strategize for brands, and much more.

How does Snowflake stand out from its competition?

Snowflake stands out as the ideal platform for organizations to execute Secure Data Sharing across their entire business ecosystem. Our cloud-built architecture provides the convenience of Data Sharing without the need to tediously move or copy a whole load of data. All it takes is for the authorized personnel to simply reference the data in a secure and controlled way. This can be easily done across regions, cloud service providers, and companies.

With Snowflake’s Data Cloud, organizations can look forward to an easy-to-use service that features multi-cloud ability and Data Sharing capability. Where billing is concerned, the service is billed per second, which basically means an organization only pays for what it uses, while computer and storage operations are billed separately. In a nutshell, utilizing Snowflake’s Data Cloud will create opportunities for seamless data collaboration, provide new business insights, and consolidate business relationships in the most cost-effective way.

Furthermore, Snowflake prioritizes maximizing performance and efficiency with an architecture that provides clients opportunities to run multiple workloads across several teams without depleting resources, be it for data engineering, data warehouse, data science, data applications, or data sharing. For companies that are still operating with on-premises data centers, moving to the cloud with Snowflake is a seamless process while start-ups that have already made the transition to the cloud can easily adopt Snowflake to enhance the management of their workload.

All these factors essentially give us the upper hand and set us apart from our competitors.

How does AI & Machine Learning assist brands to reach their target audience?

It goes without saying that all brands thrive to improve and enhance customer experience. Manual processes such as looking up and analyzing customer data to provide suitable solutions are a thing of the past. Artificial intelligence (AI) and Machine Learning (ML) have completely transformed the data landscape and help companies understand their customer’s behavior, likes, and dislikes much faster and more effectively. A data-backed solution also enables the quick processing of information that is generated to deliver an improved consumer experience.

With a detailed understanding of customer behavior, marketers are able to plan better campaigns and improve strategies in real-time. Utilizing the power and speed of AI and ML will help companies identify existing customer patterns and predict future trends which leads to more precise and effective marketing strategies.

These are the key benefits that Snowflake believes companies will gain from the implementation of AI and ML in their marketing strategies:

  • With more customer data comes clarity on customer behavior which creates avenues for impactful marketing messages.
  • Getting a better understanding of your target audience, particularly their preferred mode of communication helps deliver tailored customer experience and meet their expectations in near-real-time engagement.
  • Beyond understanding customers, companies can also identify the right channels that can effectively connect with them for desired outcomes.
  • Data obtained from AI and ML analysis provide companies the opportunity to combine insights and personalize marketing campaigns based on data specifics, to individual customers. Among the marketing initiatives where this analysis can come in handy are direct mails, websites, social media, and in-store marketing events.

Eventually, the aforementioned benefits will drive customer lifetime value via personalization and boost a company’s analytics team with greater agility and predictive analytics-driven smarter decision making, which will help in increasing the speed of ROI. Internally, it will also benefit in retaining, as well as attracting, new analytics talent looking to be a part of a set-up that embraces an architecture featuring multi-cloud and seamless data sharing capabilities.

How does cloud or data analytics take shape in the advertising/digital sector?

The advent of AdTech has accentuated the importance of data analytics. It has introduced new and more effective means for marketers to increase the visibility of their online advertisements and generate the desired response. AdTech companies can harness the power of big data analytics to measure the kind of ad responses that also indicates audience behavior which will be useful to improve targeting.

From our partnership with Accordant Media, we have witnessed the company achieving results at least twenty times faster with Snowflake’s platform compared to what they relied on before. Marketing agency Greenhouse is another partner that has flourished on our platform by leveraging data to help their clients understand the trends of their respective target audience and subsequently make result-oriented digital advertising decisions.

Another reason why data analysis is a blessing for AdTech businesses, and other companies actively pursuing advertising is that it takes into account many variables of a target customer such as lifestyle, interests, activities, etc. and channels the visibility of the ad at the right moment to ensure it has the best impact on the potential customer. In an era where people are surrounded by brands competing for their attention every moment, big data plays a crucial role for an ad to create a connection with an individual customer at the most opportune time to generate a positive response. These factors should underscore the value of data to the AdTech industry.

How does Snowflake’s real-time marketing analytics identify customer engagements across different channels?

As I’ve mentioned earlier, our cloud infrastructure is highly flexible and scalable therefore making it possible for companies to optimize their digital campaigns almost in real-time. Personalization initiatives in digital Ad campaigns are likely to increase ROI. When utilizing Snowflake’s architecture, there are no tedious methods such as balancing batch data loads with processing to generate business intelligence, business analytics, and data science. With the ability to add computing resources to clusters when required, all of these functions can simply work in tandem.

Therefore, data analysts can conveniently report on any campaign performance at any time which gives marketing teams a great advantage, allowing them to tweak messages and creative assets quickly for different segments of their audience to drive conversion and sales. In a nutshell, our goal is to help marketers realize the importance of one-to-one targeting at scale. At the end of the day, effective personalization of marketing efforts, especially on apps and websites, does result in a better user experience and potentially higher conversion rates.

How does data analytics help boost programmatic advertising?

Data-driven algorithms are crucial for media optimization to ensure the right messages are displayed to the right target audience across multiple media platforms. The basics of advertising essentially remain the same. It is still pretty much about displaying an ad to a prospective customer and a call to action. However, the challenge today is to target the right person, with the right creative message, at the right time.

As buying and selling of advertisements become increasingly automated, advertisers today are eager to adopt new channels to increase their chances of attracting potential customers in ways that do not burn a hole in their pockets. This can be achieved by leveraging Snowflake. Our cross-channel, log-level data enables marketing and campaign managers, ad buyers, and marketing analytics teams to access their data is safe and secure ways and run full-funnel attribution and improve their data analysis.

Access to data can even be done at the event level while executing a marketing campaign. One of the benefits of operating in an advanced analytics environment is that companies can store data in a single location which provides an additional layer of privacy.

Companies today are looking for the best bang for their buck. Does data analytics also include recommendations on where spending should be allocated?

Despite the rise in data analytics investments in recent years, there is still a lot of room to derive the best value from these investments. One of the biggest issues is the siloed approach of some traditional brands and their use of countless marketing channels. This requires endless monitoring processes to identify those that are effective in generating sales or other objectives set by companies. This is where the importance of data analytics comes to the fore.

Attribution models utilize data to piece together a customer’s journey and provide insights into all channels visited by a customer leading to purchase and identifying the influential and demand factors of each channel that led to the desired outcome. Companies can immensely benefit from attribution, which takes into account data for direct and indirect outcomes, to establish the true ROI of marketing investments.

How does Snowflake allay client fears on privacy and security?

Our belief is that customers should be more focused on analyzing data rather than worry about data security. Therefore, we have implemented an industry-leading security feature that protects users and accounts stored in Snowflake. End-to-end encryption and our built-in multi-factor strong authentication system ensure data is always secure, user communication encrypted, and integrated with a cloud service provider’s private networking.

We also feature a fully encrypted storage for all saved data to be in encrypted form with Snowflake handling the drivers and systems. All log-ins, transactions, and data transfers are tracked and performance reports are sent to users. Accidents can happen and in instances where data is lost, Snowflake does have options for data recovery.

Snowflake meets NIST 800-145 requirements and is also FedRAMP ready. In addition, SOC 2 Type 2, PCI DSS compliance, and support for HIPAA compliance validate the level of security for Snowflake.

Tags: Snowflake IndiaVimal Venkatram

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