Mastering Location Data – a new paradigm in network analytics
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Wireless and wired telecom providers use geocoding and location analytics for network planning and subscriber acquisition. Location data becomes even more critical during 5G deployments. For example, for fixed wireless deployment using millimeter wave (mmW) bands, which provide extremely high speeds and capacity in focused areas, operators must accurately know what the best locations are for deploying 5G small cells. Just as important is knowing what the customer locations are that will be inside the coverage area. How well it works depends on hyper-accurate geocoding and a rich set of data attributes augmenting a correct residential or business address. Typically, however, engineering, marketing and customer service use siloes and inconsistent in-house datasets, myriad data products and formats, and disparate analytical tools. The result can be costly mistakes across a range of use cases, including misplaced 5G infrastructure that blocks signals and investments in neighborhoods that aren’t a good market for 5G services. For cable operators looking to expand network penetration, errors include inefficient routing of fiber drops and overlooked occupants of near-net buildings. In this webinar, we will examine a different approach to linking latitude/longitude with an accurate address and data attributes such as building footprint, height and occupancy as well as neighborhood-level demographics. Topics covered in this presentation will include: - Challenges CSPs face today in using data for network planning, including new 5G infrastructure and optimizing existing wired networks for both end users and backhaul customers - Understanding and implementing accurate address and geocoding data across multiple use cases, including customer acquisition - How a Master Location Data approach can efficiently augment lat/long and address data with detailed attributes needed by engineers and marketers
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Mastering Location Data – a new paradigm in network analytics
- 1. Mastering Location Data – a new paradigm in network analytics
- 2. 2 5G Demands Location, Location, Location INCREASED DENSITY
- 3. 3 These upgrades have happened before, but 5G is a whole new game
- 4. has never mattered more. Where to place towers and how to structure macro and micro cells, and to assign data,
- 5. It doesn’t take much to figure out what happens if it goes wrong. 5 Are you building in the right place? Are you marketing to and servicing the right people? Are you properly provisioning the service?
- 6. 6 One tower Loss of subscribers One building Tower by Tower Device by Device 0.5% poor placement $10 billion Investment $50 million of waste
- 7. Real location intelligence is knowing where to build, who to market to, what to say, and how to get it right
- 9. Superior understanding of your customers helps you to identify and engage ideal customers and prospects, learn their behaviors, in the places that matter to them
- 10. A location-centric approach to MDM puts network providers in control. 03. Operationalize your addresses Use the ID to build a contextual view of a location for better insight. 02. A trusted ID Assign a trusted ID that is unique and persistent to each address. 01. Precision Geocoding Achieve the highest level of address integrity and positional accuracy.
- 12. Master Location Data with PreciselyID WHAT IS IT: Best-in-class Address Point geocoding dataset that is built, owned and maintained by Precisely WHY IS IT SO ACCURATE: HIGH MATCH RATE + BEST IN CLASS POSITIONAL ACCURACY Build Data Merge De-dup Standardize Link to our data Build linkable data Pre-score the country Discover additional addresses Manage data synchronization Data Transfer 55% Building Centroids (or better) 38% Parcel Centroids 3% Interpolated Locations 4% Backfill Centroids 207m Addresses 50m Secondary Addresses 193m Addressable Locations (PreciselyID) Support for POI’s in Address Matching Assign PreciselyID
- 13. Matching: How well does your geocoder handle incomplete input data? 13 Mesilla Valley Mall 88011 Input Address Output 700 S Telshor Blvd Las Cruces, NM 88011-4669 W399S6012 CRZ WI53118 Input Address Output W399S6012 COUNTY ROAD Z Dousman, WI 53118-9543 1053 Thornton Lake 97321 Input Address Output 1053 NW West Thornton Lake Dr NW Albany, OR 97321-1352 1 100 #1 10025 Input Address Output 1 W 100th Street, Frnt 1 New York, NY 10025-4857
- 14. What point does your business demand? Unit Address Point Building Centroid Parcel Centroid Street Centroid Street Interpolated
- 15. A trusted ID
- 16. IDs are better than multi-field labels 4750 WALNUT ST STE 200 BOULDER CO 80301-2532 Developer & Local Addressing Authority Local Addressing Authority & USPS Developer & Building Owner Building Owner USPS & City Government Federal & State Governments USPS Let’s dissect this addressAn address is a multi-field labelling system that is utterly unsuited for operationalization and automation. Each field is owned and updated by different entities.
- 17. We’ve assigned a Precisely ID for every address so you can stop relying on complex multi-field addresses. Remember this slide? 17 Mesilla Valley Mall 88011 Input Address Output 700 S Telshor Blvd Las Cruces, NM 88011-4669 9S6012 CRZ WI53118 Input Address Output W399S6012 COUNTY ROAD Z Dousman, WI 53118-9543 1053 Thornton Lake 97321 Input Address Output 1053 NW West Thornton Lake Dr NW Albany, OR 97321-1352 1 100 #1 10025 Input Address Output 1 W 100th Street, Frnt 1 New York, NY 10025-4857 P0000G4I6A4F P0000PB9B3L2 P0000GL1BBGUP0000IVQH0XI
- 18. Trusted IDs are essential to operationalizing addresses Operationalized addresses have been: • Cleaned, standardized, and validated • Precisely located with geographic coordinates (geocoded) • Assigned a unique, persistent ID • Enriched with additional information
- 19. PreciselyID enables data automation that adds context and improves your down stream analytics. PreciselyID ID Lookup Extended Attributes Parent / Child Type- ahead Hard to locate addresses Connected Data Portfolio Address Fabric
- 20. • All of the best address locations for use in any database, business intelligence, or location intelligence platform • This dataset is built from our Master Location Data and contains accurate and comprehensive address locations. • Each address record as been pre-verified, pre- validated, pre-standardized, pre-geocoded, and previously assigned a PreciselyID. • Additional attributes include property type, parent/child relationships. Address Fabric
- 21. Points of Interest Location Risk Data Consumer Data Property Attributes Boundaries Building Footprints Our Connected Data Portfolio Location Data Ecosystem Operational Impact Network performance Sales and Marketing Optimization 5G buildout Subscriber analytics PreciselyID
- 22. Points of Interest Location Risk Data Consumer Data Property Attributes Boundaries Building Footprints Add your data to analytics PreciselyID Device IDs Signal Strength Predicted Coverage Competitive fiber Data consumption by device Average monthly bill
- 23. Straight-though-Processing for Operationalizing Addresses Address Geocoding Interactive Geocoding (Type-Ahead) Reverse Geocoding Operationalized Address • Cleaned / Standardized (postal format) • Validated (deliverable) • Geocoded • PreciselyID added Enrich with data • Risk Data • Property attributes • Points of interest • Demographic data • Building footprints • Boundaries ID lookup Business impact • Network performance • Sales and Marketing Optimization • 5G buildout • Subscriber analytics
- 24. Leveraging location enrichment and ML to pre-qualify every location in a market 24 Geocoding, Enrichment, and Scoring Elastic Autoscaling Microservices Store the PreciselyID + Network ID + Signal Quality Score + 911 data + Lat/Long + Tax Info Amazon Cloud Toolset Mobile Data Hotspot Data Public Data Property Data Model best signal by property type and location Geo-enrich with Property attributes Geocode and generate a PreciselyID Score the entire market Geocode Geocode candidate address and generate a PreciselyID DBLookup Gather candidate details by PreciselyID ApplicationLayer
- 25. Questions?
Editor's Notes
- There are two reasons for this. The first is technical. The wavelengths that operate as part of the 5G specification, especially in the ultra-dense 30-100GB range, are more attenuated by physical obstructions. As a result. Microcell placement needs closer proximity between devices in order for 5G to deliver on its expected network speeds. For the millimeter waves in the ultra-dense spectrum, this requires attention to physical realities – building material, distance from cell, knowledge of what people will do with the improved bandwidth, even the weather, as rain can interfere with wave transmission. You’re going to have more frequent handoffs as a result. And each handoff is a potential lost call or delayed signal. ABI Research just noted in their Reality Check on the 2019 Mobile World Congress that “everyone” agrees” that antennas are key to successful 5G deployment. In addition, despite some vendor claims that existing base stations can be upgraded to 5G, it’s far more likely still be deployed as an overlay, as existing stations will still be utilized for 4G. When it comes to getting this all to work, location, knowing where to place a cell and how much bandwidth to supply, will be how Telcos gain a strategic advantage in the new world of 5G. There’s a shift here between writing in the third person to writing in the second person. Why? Two reasons: first, it’s useful in challenger to have a tone that isn’t abstracted, and it’s impossible to talk about the state of the industry entirely in the second person. So state of the industry is third person, impact on person being pitched to is second person. Second, it’s a technique called interpellation – it works by describing the subject position that the writer/speaker/salesperson wants the audience to see itself in. The simplest way of doing it is selective use of second person. I don’t recommend it for a blog post, but it works well as a technique for a pitch or keynote (the latter depends somewhat on audience).
- We might be tempted to think this is business as usual, just another incremental upgrade in mobile technology. It’s not. As Yogen Patel, head of Amdocs open network marketing, pointed out at this year’s Mobile World Congress: previous upgrades have largely been about capacity. But with 5G, the real value will be quality of service. The higher speeds and lower latency will combine with new services to allow providers to differentiate based on quality of service in more obvious ways more obvious ways, and in ways that matter to consumers.. This is a big change, and whenever there’s a shift like this in the marketplace, new winners emerge, and old winners fall through the cracks. This happens with every major technology shift. HD changed who dominated the television market. The shift to mobile changed who made money by supplying information and services Now a similar change is happening in TELCO. And it’s happening amidst massive capital expenditures for infrastructure like fiber, and the cost of securing access to bandwidth.
- As a result, the question of where to place towers and how to structure macro and micro cells, and to assign data, has never mattered more. The building of infrastructure, like the laying of fiber optic cable, or the placing of 5G cells, will determine signal strength and separate the products and service that matter from those that don’t. In effect, 5G transforms a tactical issue into a primary strategic concern. If you’re still treating location intelligence as a tactical issue, or as an operational concern, you’re doing 4G thinking in a 5G world.
- Every TELCO is going to be making huge investments in infrastructure. You’re going to make those investments. The question is whether you’re going to make the right ones. The answer to that will depend on three things: are you building in the right place, are you marketing to and servicing the right people, and are you properly provisioning the service? It doesn’t take much to figure out what happens if it goes wrong. You build in the wrong place and a building interferes with your signal, and you lose customers. You don’t understand your audience and how they use their devices, and as a result you don’t have enough bandwidth in the right spot, or you have too much where you don’t need it. You lose money. You provision poorly and waste a 200-300 dollars every time you send a crew out to see why a wireless signal isn’t working inside a home as advertised. You lose customers and money—one service call at a time. Again…the issue with using second person seems accusatory. It’s the wrong tone. I’m happy to turn this over to the wisdom of the committee. I absolutely understand the concern here. On the other hand, rational drowning is the moment in challenger when it pays to be a bit more confrontational.
- When we’re talking billions of dollars of investment, even a small error racks up a pretty disturbing bill. Even if .5% of placement is done poorly – and I think we can agree that’s an artificially low number – it means that a 10B investment results in 50M of waste. It doesn’t happen all at once. It happens tower by tower, $2-3 million at a time, station by station, cell by cell. If any of these are placed incorrectly, if they can’t provide the right level of service, if they have to be replaced or supplemented because of inefficient coverage, the costs will pile up, and pile high. It doesn’t end there. Those unforced errors go hand in hand with lost opportunities. An apartment building that gets insufficient coverage, and costs you 50 new subscribers at $600 per year, or an office park with insufficient signal, that costs you 10 small businesses running at $5000 annually. Now imagine that happening over and over again. Imagine losing 4G LTE customers because their friends aren’t happy with your 5G coverage. Those aren’t rounding errors. They’re the annual margins. They’re the time to ROI.
- The good news is that there’s a better way to do this, a smarter way, a way that takes advantage of the latest technologies and years of experience and knowledge. You need a comprehensive approach to location intelligence, one that can understand location in three dimensions and then also understand the people who live and work and move through those places, and that can map the activities those people undertake, device by device. You need to know the shape of building, type of building, topology, the digital traffic passing through that location, the likely demographic and psychographic factors that will influence present and future data consumption in that location. In a 5G world, where signal must be closer to the people who use it, you really need to know the people, where they are, and what they do. Location intelligence is more than just about looking at a map. Real location intelligence is knowing where to build, who to market to, and how to get it right.
- If you can take all that information and integrate it together, then you can build a digital twin before you invest in the build-out; you can create a simulation that can validate or modify strategy and inform execution. You can learn, and adapt, without wasting funds on bad builds or the wrong audience.
- [---- Solution / Marketing ----] That superior understanding of your customers helps you identify who to market these new services to, who can afford them, who wants them, even who thinks they need them. It can target growth in areas or populations in IoT or new streaming services. It can look at city zoning, economic development data, school locations, and so much more.
- Product: Master Location Data
- ….Computerization leads us onto use-cases for addressing and geocoding An address is a multi-field labelling system where each field is owned and maintained by different entities. These fields frequently change and the address itself has multiple purposes. Addresses are necessarily highly fault tolerant and therefore utterly unsuited for operationalization.
- Now that we have an ID, the real fun can begin. Let’s start to operationalize your addresses.
- Touch on all items on the slide. We have additional slides on Connected Data and Address Fabric. ID Lookup: The ability to lookup an ID (preciselyID) and return the address Extended Attributes: Easy to provide additional property centric information that informs decision making Parent/Child: The relationship between primary and secondary addresses Type-Ahead: Human interactive lookup of addresses Hard to locate Addresses: Known addresses with poor locations Connected Data Portfolio: Rich data portfolio connected with a high degree of integrity (see later) Address Fabric: A raw version of the data inside the geocoder Coming Soon History: Currency of an Address and whats happened to it so far Additional Points: Different types of locations, not just the best we have World Premium Point of Interest: Included as part of the geocoding process to match business name not just street address Genealogy: A linkage file that describes the addresses relationship to sub-buildings, rooftops (if different) and parcels)
- Use Address Fabric to count buildings within an area of interest. Other pieces of information contained on address records include FIPS code and Census information Parent/child relationships for primary and secondary addresses (units, suites, apartments, etc.) Property type (Business or Residential)
- We have off the shelf data (footprints, POIs, boundaries, etc.) available to quickly enrich your addresses. This is enabled by the pbKey feature within MLD and the fact that we have pbKeys on our enrichment data. Enriched address provide more context and serve as a better starting point for business operations/challenges/analytics/etc. that appear on the right side of this slide.
- We have off the shelf data (footprints, POIs, boundaries, etc.) available to quickly enrich your addresses. This is enabled by the pbKey feature within MLD and the fact that we have pbKeys on our enrichment data. Enriched address provide more context and serve as a better starting point for business operations/challenges/analytics/etc. that appear on the right side of this slide. Device IDs Signal strength Predicted coverage Data consumption by device Average monthly bill Competitive fiber
- Challenge was to classify (Fiber-lit Predict vs. Non) a highly multi-dimensional and imbalanced information of location-enriched 1000-plus-col dataset. So we two approaches to predict next-gen fiber-lit addresses. NeuralNet based classification and SVM-based novelty detection. NN Classification Dropped numeric columns with high missing rate and Dimension Reduction (DR) Performed RFE-based DR again on categorical variavles Concatenated reduced numeric columns with categorical variables Split the data 60-20-20 (Training-Validation-Test) Applied 3 layers of NN (Relu on 1st and 2nd) and Sigmoid on 3rd Applied Binary Cross-entropy as the Loss function Batch size of 1K/epoch for 100 epoch Result as displayed - For negative class we get the f1-score of 0.98 (expected as this is the majority) and positive class a score of 0.92 which is a good result (Google precision, recall and f1-score) Precision is perfect but recall is a bit lower 0.85 i.e. 85% of the actual ones are captured by this prediction. And 100% of the prediction are the true ones. SVM Repeat steps 1-4 above followed by a one-class SVM since this was a PU task by nature since the -ve were unlabeled building rather than true negatives. Future: For NN try multiple layers with activation function combination Try ensemble of models