How Onalytica Drives Operational Efficiency in Influencer Relationship Management

Zuzanna Pasierbinska-Wilson

For a textbook example of how DataSift is helping partners aggregate, process and deliver social data—read on. Onalytica’s solutions surface relevant influencers for their clients, helping them to manage those relationships over time. Working with DataSift, Onalytica generated cost savings through less reliance on an internal data center, and eliminated data gaps for an enhanced end-user experience.

So what’s behind this partnership success? Onalytica helps leading brands and agencies systematically manage their relationships with influential stakeholders such as investors, journalists, regulators, thought leaders and bloggers, with a view to scaling their influence and deploying their resources more efficiently.

The company’s Influencer Relationship Management solution allows customers to reach the right people at the right time with the right message at scale, by building relationships with key stakeholders and managing them over time. Influencer Identification services allow customers to surface credible and relevant influencers and subsequently create influencer marketing programs.

This measurement is unique in that it focuses on the calculation of a network score. Based on a similar model to page rank, this algorithm uses social data to assign influence in a given topic to an individual, as that individual interacts with others in that topic, they contribute some weight to these connections. In this way a very targeted, relative and relevant influence model can be built around any topic.

DataSift efficiently collects social data signals

To create these models, Onalytica needs access to a ready supply of social media interactions and the associated metadata that provides the details necessary to calculate these scores. After initially beginning to build out their own data center, Onalytica quickly realized a more efficient approach would be to work with a data partner that could provide a cost efficient and scalable infrastructure with:

  • An approachable UX to simplify the process of working with a complex platform
  • The ability to easily switch on a variety of sources to expand the influence model cross-channel
  • An accessible historical data store to pull on when creating reports for new clients

With DataSift, Onalytica is able to collect the social data signals they need to provide their customers with influencer identification and relationship management capabilities.

Several factors made DataSift the right data partner for Onalytica—mainly focused on increased operational efficient:

Unified Stream API. Consuming data from DataSift gives Onalytica a long-term benefit of exploring the addition of new data sources. Because interactions from all data sources are normalized and delivered in a single API, activating a new data source would take less development investment on Onalytica’s part, giving them more range to experiment and expand.

Historics. Influence measurements often being by analyzing a period of time and then adapting and improving the scores over time. So having easy access to historical data to run a report when a new client or project comes up is critical. Being able to apply the same filter to a historic or real-time query decreases the overall time and effort required.

Data Buffering. Using data buffering reduces the cost of downtime for Onalytica by ensuring nothing is lost. Additionally, being able to deliver data to multiple destinations means that Onalytica can store data in the cloud, for example, into Amazon S3, keeping it there until it’s needed and reducing strain on the on-premise data center.

Since working with DataSift, Onalytica has generated cost savings associated with less reliance on an internal data center. The company has also eliminated gaps in their data caused by data center downtime, delivering a better end-user experience to their customers.

Onalytica’s spokesperson concluded, “We’ve significantly lowered our risk in terms of data. It doesn’t matter if our data center needs to stop for a few hours or if something breaks down because we have a consistent flow of data from DataSift going into a location where it’s being collected.”


Zuzanna Pasierbinska-Wilson

Written by Zuzanna Pasierbinska-Wilson

Zuzanna is SVP, Marketing at DataSift. You can follow her @fattypontoonski.

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