The following is an excerpt from our white paper on Adopting a Hub Driven Workflow to Automate Ad Sales. This is part three, you can read part one here and part two here. To download the entire white paper, please visit this page. Enjoy!
Adopting a hub-driven workflow provides the multi-faceted means to centralize data from multiple systems to improve workflow efficiency, as well as support a more consultative sales approach. The hub, or lead system, serves as the engine used to drive the entire automated workflow.
Operating as the nucleus, it continuously pumps data in and out, allowing for one master set of data to flow freely throughout the entire end-to-end workflow. The cohesive movement within the workflow pro- vides each of the isolated departments the ability to access, manage, and interact with accurate data in real-time.
Not only are there multiple sets of data in the many disparate systems throughout an enterprise, there’s also several types of data collected within each system. When this data gets merged and purged several times, the information tends to get mixed up or misaligned. For example, accounting will collect and maintain more specific billing information tied to each record and sales may capture more relevant relationship data, such as a contact’s birthday (why not?). When exported from an accounting and sales system, the core contact and account data will merge and appear normal, but if those specific fields from each of the systems are not carried over in the new merged loca- tion, the information is lost.
Solutions to managing workflows that span multiple systems have involved using Dropbox or flash drives between departments, importing/ exporting data, or implementing integration points using APIs, or hard-coding. These bandages on legacy systems allow for the data to be merged, but fall short when it comes to unifi- cation. Merging is often short-lived and gives the user a more immediate view and interaction to the data, whereas unify- ing the data brings the records together holis- tically from that point forward for the longterm. It also prevents information from getting lost in the shuffle.
When deploying a hub environment, data is aggregated at the onset and all records are normalized, allowing the system to prompt users to unify similar records (i.e. not create an entirely second record if the company name is misspelled, for example). The unified data becomes the master record for each contact, account, sales, and operational transaction, and from that point forward is managed and viewed as such. If a contact record is updated by one user, it is automatically reflected across the enterprise in real-time anywhere that data can be accessed.
Beyond master records, the hub further automates the flow of data as relevant to business, ensuring
a more progressive workflow. For example, an AE on the road may find a few new lead opportunities and then enter their information into the hub-driv- en workflow. A new lead card is created. The Sales Manager receives an alert notification to approve and assign the new lead for the AE. This simple and automated step helps:
Again, this streamlines the processes up and down the chain, as other departments are able to access and add to the record as opposed to needing to create a new one for their own purposes, causing duplications.
Another example is the AE’s ability to view inventory availability from the operation’s ad server in real-time. To some extent this equips the AE with a roadmap for selling, i.e. what inventory is available to sell, what is prime inventory, what is the rate, etc. This access eliminates the contact made from sales to operations to check on inventory availability, as described previously.
The data associated with a master record may span across multiple markets, revenue channels, and contain multiple contacts, however because it is managed by the hub, users are able to view all the data they need from one accurate source.
Additionally, the data to the Nth degree that the advertiser is looking for may be captured and / or pulled in from a third-party source into the hub. With this information in one place, sales can drill-down to see how an account is performing, what their traditional versus digital ad spend is, if an account is not spending in a category such as mobile, or more. Capturing and viewing data instantly is imperative to providing a comprehensive and holistic analysis to all users. And just as the data is aggregated to provide summarized views, it can also be dissected to provide segmented insights as needed, such as digital sales compared to television sales, market comparisons, or sales territory trends.
Providing AEs with more in-depth views of accounts, contacts, and analytics allows them to apply a more consultative sales approach, which is what they need to be successful in selling more fluid and out-of-the-box ads. Furthermore, getting that data into the system early is key to adopting process and leverag- ing the implied technology. It also provides a better picture to anticipated sales on the front end and insightful metrics on the back end.
Relying on master data to generate reports provides similar value, whereby, the results are more concise, pulling from one source and in real-time. As you can imagine, extracting such aggregated and accurate data, saves hours of time typically used to produce compounded Excel reports.
Fostering a hub-driven environment shifts the dynamic of the workflow from reactive to proactive. Rather than chasing down a process to add records, record info, and analyze the data (which is often manual at best), those tasks are automated. The lead system in the hub environment prompts users to suggested next steps and recommended actions to ensure a progressive workflow.
Key to capitalizing on the automated intelligence of the workflow is ensuring the right data is captured and accessible. As Jon M. Jachimowicz articulates in A 5-Step Process to Get More Out of Your Organi- zation’s Data, “think through what kind of data will be useful to collect, and then collect it — systemat- ically. Have regular conversations with people from
throughout the company to identify what questions are pressing and what kind of data you may need to answer those questions.” Putting in the upfront work to know what data is relevant and improve upon its quality is fundamental to getting the answers you need from the data. Jachimowicz states, “data analy- sis requires data processing abilities.”3
Specific to media ad sales, users may want to think through the types of alert notifications they want to receive that will support their efforts and in turn
increase revenue. Doing so will ensure that informa- tion is captured appropriately and leveraged via the system’s automation. For example, sales may want to know 10 days in advance of a campaign coming to an end, so that they may in turn reach out to the advertiser to extend or brainstorm the next one. Or in another example, if a digital campaign is pacing ahead, the AE can be alerted to reach out to advertising customer to renew the campaign.
Come back next week for the continuation of this article. Can't wait? Download the entire white paper here.